Determining relative air quality impacts of various personal vehicle

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SCENARIOS........................................ 28 7.1 Baseline air quality............................................................................................. 28 7.2 Impacts of vehicle scenarios on pollutant emissions ......................................... 29 7.3 Air quality impacts of vehicle scenarios............................................................ 31 8. CONCLUSIONS....................................................................................................... 35 9. RECOMMENDATIONS........................................................................................... 36 10. REFERENCES.......................................................................................................... 37 Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 3 March 28, 2008 List of Tables Table 1. Emission factors for vehicle operation and start-up, for an average light- duty vehicle estimated for the year 2050, and the contribution of normal operation and start-up emissions to total emissions from light-duty vehicles .................................................................................................................7 Table 2. Technical specifications for the 2000 Toyota Prius..............................................8 Table 3. Emission factors for the 2000 Toyota Prius (from Graham, 2006)......................8 Table 4. Hourly trip frequency distribution as a function of trip length. Values based on information collected by EPA in Baltimore, Maryland; Spokane, Washington; and Atlanta, Georgia......................................................12 Table 5. Hourly distribution of trip starts and estimated hourly cumulative number of trips of an average light-duty vehicle assuming the start of daily activity at 6 am...........................................................................................14 Table 6. Cumulative mileage per trip length bin, CMT VMT,h , assuming hourly distribution of trips presented in Table 5............................................................15 Table 7. Distribution of trips that exceed the all-electric range of 40 miles and that require the use of the internal combustion engine.......................................16 Table 8. Percentage of total trips and total miles that require the use of the internal combustion engine, the total electricity needed to re-charge batteries, and the total power needed using 8-hour and 24-hour re- charging cycles, for four different PHEV cases: PHEV8, PHEV20, PHEV40 and EV.................................................................................................18 Table 9. Total emissions from distributed generation to produce electricity for a pure electric vehicle fleet in the SoCAB by the year 2050 (in tons per day), emissions from DG per mile, and DG emission factors relative to the HEV emission factors...................................................................................22 Table 10. Source apportionment of the 2023 emissions inventory for the South Coast Air Basin of California .............................................................................27 Table 11. Source apportionment of the 2050 emissions inventory for the South Coast Air Basin of California, using 2023 emissions inventory and extrapolating on-road emissions using EMFAC estimates.................................27 Table 12. Maximum concentration of pollutants for the 2050 baseline case and California Ambient Air Quality Standards (CAAQS)........................................28 Table 13. Maximum 1-hour peak O 3 concentration in all cases and maximum differences in peak O 3 and 1-hour average O 3 concentration with respect to Baseline...........................................................................................................32 Table 14. Maximum 24-hour PM 2.5 concentration in all cases and maximum differences in 24-hour PM 2.5 concentration with respect to Baseline.................32 Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 4 March 28, 2008 List of Figures Figure 1. Trends in on-road mobile emissions, fuel usage and vehicular activity estimated by EMFAC version 2.2 (April 2003) for the period 2010 to 2040.....................................................................................................................7 Figure 2. Hourly distribution of number of trips and vehicle miles traveled of all light-duty vehicles estimated for the South Coast Air Basin of California in the year 2050................................................................................13 Figure 3. Hourly distribution of number of trips and vehicle miles traveled that require the internal combustion engine of PHEVs in four different scenarios: PHEV8, PHEV20, PHEV40 and Baseline.......................................17 Figure 4. Distribution of technologies for DG implemented in the SoCAB for the year 2030 (from Samuelsen et al. 2008). LTFC: low-temperature fuel cell; HTFC: high-temperature fuel cell; MTG: micro-turbine generators; NGIC: natural gas internal combustion engines; TURB: gas turbines; HYBR: fuel cell-gas turbine hybrid system.......................................21 Figure 5. UCI-CIT Airshed modeling domain of the South Coast Air Basin of California...........................................................................................................25 Figure 6. Baseline pollutant concentrations in the year 2050 in the South Coast Air Basin of California: (a) peak ozone concentrations, (b) 24-hour average PM 2.5 concentrations............................................................................29 Figure 7. Total light-duty vehicle emissions of criteria pollutants from all scenarios relative to baseline light-duty vehicle emissions in 2050..................30 Figure 8. Total basin-wide emissions of criteria pollutants from all scenarios relative to baseline basin-wide emissions in 2050 ............................................30 Figure 9. Differences in peak ozone concentration in various vehicle scenarios with respect to the 2050 baseline: (a) All electric vehicle case without emissions from electricity production; (b) All electric vehicle case with in-basin electricity production via distributed generation; (c) All hybrid electric vehicle case; (d) All plug-in hybrid electric vehicle case without emissions from electricity production; (e) All plug-in hybrid electric vehicle case with in-basin electricity production via distributed generation; (f) All plug-in hybrid electric vehicle case with in-basin electricity production via distributed generation and no start-up emissions...........................................................................................................33 Figure 10. Differences in 24-hour average PM 2.5 concentration in various vehicle scenarios with respect to the 2050 baseline: (a) All electric vehicle case without emissions from electricity production; (b) All electric vehicle case with in-basin electricity production via distributed generation; (c) All hybrid electric vehicle case; (d) All plug-in hybrid electric vehicle case without emissions from electricity production; (e) All plug-in hybrid electric vehicle case with in-basin electricity production via distributed generation; (f) All plug-in hybrid electric vehicle case with in-basin electricity production via distributed generation and no start-up emissions...........................................................................................................34 Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 5 March 28, 2008 1. INTRODUCTION There is considerable pressure in the state of California and throughout the world to consider, promote, and even mandate alternative vehicles and fuels to improve air quality and to reduce greenhouse gas emissions and fuel consumption. Ozone and other criteria pollutant concentrations as well as particulate formation and transport will be impacted by changes in vehicle types, miles traveled and emissions as well as atmospheric physics and chemistry. A thorough and scientifically sound analysis of both the emissions and atmospheric physics and chemistry is required to understand the environmental impacts and to make wise decisions amongst the possible alternative vehicle and fuel options. The current project develops detailed spatially- and temporally-resolved emissions inventories for personal vehicle and fuel options and assesses environmental impacts with a state-of-the-art air quality model. Previous studies evaluated air quality impacts of hybrid-electric and fuel cell vehicles in the US relative to the existing conventional vehicle technology (Colella et al., 2005, Jacobson et al., 2005). These studies assumed that emissions from hybrid vehicles were lower than conventional vehicles proportionally to their respective gas mileage. Results showed moderate improvements in air quality due to hybrid-electric vehicle implementation. Recently, plug-in hybrid electric (PHEV) have received major attention as General Motors and Toyota are developing their first PHEV models to be commercialized by 2010. Based on the recent developments, PHEV technology is closer to be commercialized than fuel cell vehicles. In addition, development of PHEV vehicles is helping the development of battery technologies, which in turn, will help the development of battery-electric vehicle models in the future. This report presents results from a rigorous study that includes development of spatially and temporally resolved emissions scenarios for various alternative vehicle options. Resulting emissions fields are included in detailed simulations of potential air quality impacts using a comprehensive atmospheric chemistry and transport model solved on a 252-node super-computer. The predicted air quality impacts are then used to evaluate the relative air quality impacts of alternative vehicle options involving battery- electric, hybrid-electric and plug-in hybrid-electric technologies in the South Coast Air Basin in 2050. Information on vehicle activity for the SoCAB is used to develop detailed performance characteristics and emissions inventories for each vehicle and fuel type option. Air quality impacts are then determined by simulation of the atmospheric chemistry and transport for each case. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 6 March 28, 2008 2. PERSONAL VEHICLE TYPES The present study analyzes the effect of widespread implementation of vehicle hybrid technologies on air quality, relative to the current technology mix for automobiles. The methodology consists in assuming that all light-duty automobiles (LDA) are substituted by hybrid electric vehicles, which can incorporate plug-in capabilities, or with pure electric vehicles. This section describes the vehicular options considered in the present study. 2.1 Baseline Light-Duty Automobile (LDA) The baseline light-duty automobile (LDA) assumed in this study corresponds to the automobile mix that the EMFAC model estimates will be present in the SoCAB in the year of study, namely 2050. The EMFAC model is developed by the ARB, and uses information on vehicle activity from the Department of Motor Vehicles and the California Transportation Department. The total emissions from vehicles can then be calculated using emission factors derived from vehicle testing. These emission factors depend on the number of starts, the ambient conditions and the speed of the vehicle, among other factors. Results from the EMFAC model provide emissions from vehicle operation, as well as evaporative emissions of VOC, and particle emissions from braking and tire wear (ARB, 2007). Figure 1 shows the relative change in vehicular activity, emissions from on-road mobile sources and fuel use for the period 2010-2040. Although the number vehicles, trips and vehicle miles traveled are estimated to increase, emissions of criteria pollutants are expected to decrease due to reduction of vehicle tailpipe emissions. This reduction is caused by the progressive market penetration of low-emitting vehicles, and the gradual retirement of higher-emitting older models. Table 1 presents the emission factors for an average light-duty automobile for the year 2050. The emission factors are disaggregated into two factors: (1) emission factors for normal operation, i.e. emissions from driving, and (2) emission factors for start-up emissions. In addition, Table 1 presents the contribution of operation and start-up emissions to total emissions from LDA. More than 85% of emissions correspond to normal operation, whereas start-up contributes to less than 15% to total LDA emissions. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 7 March 28, 2008 Figure 1. Trends in on-road mobile emissions, fuel usage and vehicular activity estimated by EMFAC version 2.2 (April 2003) for the period 2010 to 2040. Table 1. Emission factors for vehicle operation and start-up, for an average light-duty vehicle estimated for the year 2050, and the contribution of normal operation and start-up emissions to total emissions from light-duty vehicles Emission Factors Total contribution LDA operation LDA start-up LDA operation LDA start-up (g/mile) (g/start) (%) (%) VOC 0.063 0.027 92.60 7.40 NO X 0.032 0.026 86.76 13.24 CO 0.545 0.518 84.87 15.13 SO X 0.004 -- 100.00 -- PM 2.5 0.014 0.007 91.76 8.24 2.2 Hybrid Electric Vehicle (HEV) The hybrid electric vehicle considered in this study is based on the 2000 Toyota Prius. The specifications for this model are presented in Table 2. This model has been upgraded with more powerful engine and electric motor in subsequent versions. However, emissions from newer versions are not readily available. Hence, emissions from the 2000 Toyota Prius are used in this report to estimate the emissions from hybrid vehicles. These estimates could represent an upper bound for emissions as newer 0 50 100 150 2010 2020 2030 2040 Year % Vehicles VMT/1000 Trips Total ROG Total CO Total NOx Total CO2 Total PM10 Total SOx Gasoline Diesel Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 8 March 28, 2008 versions of hybrid vehicles will eventually emit at a lower rate. The emission factors for the 2000 Prius are presented in Table 3. As there is little information on start-up emissions from HEV, this study assumes the same start-up emission factors as in the case of LDA. Furthermore, as current models of Prius are certified as AT-PZEV, which implies that these vehicle guarantee zero evaporative emissions for the first 150,000 miles, evaporative emissions from HEV are neglected. Further studies on vehicle emissions will help develop a better understanding of emissions from HEV, both from normal operation and start-up emissions. Table 2. Technical specifications for the 2000 Toyota Prius Specifications Value Curb Weight: 1254 kg Engine Specifications: 1.5 L inline 4 cylinder 52 kW at 4500 rpm 111 Nm at 4200 rpm Electric Motor: 33 kW at 1040-5600 rpm 350 Nm at 0-400 rpm Batteries: NiMH, 228 cells at 1.2 V each Mileage (city/hwy): 4.5/4.6 L/100 km Emissions control: three-way catalyst Table 3. Emission factors for the 2000 Toyota Prius (from Graham, 2006) Prius 2000 (g km -1 ) a CO 0.070 NO X 0.008 NMHC 0.004 NMOG 0.004 HCHO 0.0001 PM 0.004 TC 0.0002 2.3 Plug-in Hybrid Electric Vehicle (PHEV) Future plug-in electric vehicles have the potential to allow for all-electric range driving cycles for daily average trip mileage. Some automakers are developing architectures that would allow an all-electric range of 40 miles, which would meet the daily range for an average passenger vehicle. Such range would imply that PHEV would be a truly flex-fuel vehicle, since the vehicle could achieve the daily mileage with electric propulsion only, as well as with the internal combustion only, or a combination of both. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 9 March 28, 2008 However, there remain some challenges that have to be overcome until a 40-mile range is achieved. Recently, Toyota announced that a first commercial PHEV version of the Prius will be available by 2010, with all-electric autonomy of 8 miles. General Motors is developing the GM Volt with the expectation of meeting the 40-mile all-electric range, although it is still facing challenges with the battery. This report analyzes the emissions from PHEV with different all-electric ranges. In general, control strategies for PHEV are design in a way that there is an all-electric range, in which the state of charge (SOC) of the battery is depleted down to a lower limit. This driving cycle is generally termed as charge-depleting mode. Once this lower limit is achieved, the engine is turned on so that the SOC is sustained. Such condition is termed as charge-sustaining mode. Hybrid vehicles operate in charge-sustaining mode exclusively. The all-electric range of the PHEV is determined by the size of the battery, the lower limit for the SOC before the vehicle goes into charge-sustaining mode and the power and energy demand during the driving cycle. Recent studies suggest that PHEV20 (PHEV with 20-mile all-electric range) would reduce significantly the consumption of oil, but the estimated high capital costs for longer all-electric ranges would be hardly justified by the savings in fuel consumption. However, there is a high uncertainty in the future price of oil that can affect the economics of PHEV. For the present study, all-electric ranges of 8, 20 and 40 miles are analyzed. The Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Test (HWFET) cycles are used currently by the US Environmental Protection Agency to determine urban and highway gas mileage for vehicles. These two cycles require an energy demand of 5 kWh and a peak power of 45 kW for an all-electric range of 20 miles. Energy and power requirements for 8-mile and 40-mile all-electric ranges can be extrapolated linearly. Some studies suggest that UDDS and HWFET cycles misrepresent present urban and highway driving conditions and that the Unified Driving Cycle 3 also known as LA92 3 and the US06 cycle, which is part of the Supplemental Federal Test Procedure, represent better up-to-date driving conditions. These two newer cycles correspond to more aggressive driving behaviors that would require up to 7.5 kWh of total energy and nearly 150 kW of peak power for an all-electric range of 20 miles (Markel and Simpson, 2005). The UDDS/HWFET and the LA92/US06 energy requirements are used herein as a lower and upper bound, respectively, for the electricity demand for plug-in hybrid vehicles. Longer all-electric ranges do not imply necessarily downsizing of the internal combustion engine of the PHEV. On the contrary, there is a minimal power requirement for the engine of a hybrid configuration based on performance criteria (Simpson, 2005). As a result, this study assumes that the combustion engine for all the PHEV models is the same as in the 2000 Toyota Prius. Consequently, emissions from PHEV in charge- sustaining mode are equivalent to the emissions from HEV. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 10 March 28, 2008 2.4 Pure Electric Vehicle (PEV) Electric vehicle models, such as the General Motors EV1 and the Toyota RAV4EV, have proven mileage range over 100 miles. Such mileage range implies a battery storage capacity of nearly 40 kWh, assuming vehicle electricity consumption of 375 Wh/mile. For this study, no considerations are made in terms of the battery size or cost. The PEV are assumed to consume 7.5 kWh in a 20-mile range for the LA92/US06 cycle, and this level of consumption is used to estimate the total needs of electricity for the PEV. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 11 March 28, 2008 3. VEHICLE ACTIVITY Information on vehicle activity, such as hourly distribution of trips and trip length, is necessary to estimate the average mileage of the vehicle fleet considered in this study. For cases in which PHEV are considered, hourly vehicle activity will determine the fraction of vehicles that will be able to operate in purely electric mode, as well as the portion of vehicles that will need to operate in charge-sustaining mode once the all- electric range has been attained. These estimates on battery use and engine use will allow calculating emissions from charging batteries and from HEV operation. The EMFAC model uses information on daily trip frequency based on California Transportation Department, and hourly vehicle activity collected by the EPA in three different metropolitan areas: Baltimore, Maryland; Spokane, Washington; and Atlanta, Georgia. The pondered values of trip frequency distribution used by EMFAC are shown in Table 4. Based on current information of vehicle registration from the department of motor vehicles of California and travel surveys by Caltrans, EMFAC projects for the year 2040 a total of 2.23×10 8 miles traveled by light-duty vehicles and a total of 4.19×10 7 daily trips. Using linear extrapolation, total number of daily VMT and trips in 2050 increase up to 2.39×10 8 and 4.48×10 7 , respectively. Then, hourly distribution of trips and VMT 3 shown in Figure 2(a) and (b) 3 are obtained using the trip frequency distribution presented in Table 4, and the total daily trips and VMT. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 12 March 28, 2008 Table 4. Hourly trip frequency distribution as a function of trip length. Values based on information collected by EPA in Baltimore, Maryland; Spokane, Washington; and Atlanta, Georgia. Vehicle Miles Travelled (VMT) Range Bins TIME < 1 1 0 5 5 0 10 10 0 15 15 0 20 20 0 25 25 0 30 30 0 35 35 0 40 40 0 45 > 45 (hour) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0 0.18 0.40 0.11 0.06 0.00 0.01 0.05 0.03 0.00 0.00 0.00 1 0.13 0.14 0.11 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.00 2 0.01 0.04 0.06 0.03 0.00 0.00 0.01 0.00 0.00 0.00 0.00 3 0.01 0.08 0.05 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4 0.03 0.11 0.03 0.05 0.06 0.00 0.00 0.00 0.00 0.00 0.00 5 0.01 0.17 0.09 0.09 0.05 0.03 0.00 0.00 0.00 0.00 0.00 6 0.28 0.61 0.36 0.19 0.17 0.13 0.06 0.00 0.00 0.01 0.07 7 1.08 2.34 1.03 0.59 0.22 0.19 0.13 0.09 0.00 0.01 0.03 8 1.12 2.21 1.35 0.40 0.20 0.23 0.08 0.01 0.00 0.01 0.02 9 1.25 2.14 0.84 0.26 0.14 0.05 0.00 0.01 0.01 0.00 0.01 10 1.34 2.34 0.73 0.37 0.09 0.15 0.01 0.03 0.01 0.00 0.00 11 2.19 3.32 1.15 0.24 0.14 0.08 0.03 0.01 0.00 0.00 0.03 12 2.72 3.83 1.03 0.43 0.18 0.04 0.05 0.03 0.01 0.00 0.00 13 1.76 3.45 1.07 0.26 0.19 0.06 0.05 0.03 0.03 0.01 0.02 14 2.02 3.37 1.14 0.38 0.19 0.14 0.06 0.01 0.04 0.00 0.04 15 2.36 3.10 1.39 0.37 0.26 0.15 0.04 0.04 0.01 0.01 0.02 16 1.88 3.16 1.33 0.65 0.15 0.13 0.05 0.06 0.01 0.00 0.01 17 1.90 3.46 1.45 0.40 0.29 0.20 0.08 0.05 0.04 0.03 0.00 18 1.80 3.00 0.88 0.37 0.10 0.17 0.03 0.03 0.00 0.03 0.01 19 1.49 2.34 0.73 0.32 0.10 0.05 0.03 0.04 0.01 0.01 0.00 20 0.96 1.39 0.64 0.26 0.06 0.03 0.06 0.00 0.01 0.00 0.01 21 0.80 1.19 0.43 0.26 0.14 0.06 0.04 0.03 0.03 0.00 0.00 22 0.54 0.82 0.36 0.19 0.09 0.04 0.01 0.03 0.01 0.01 0.00 23 0.59 0.68 0.26 0.08 0.05 0.03 0.05 0.00 0.03 0.00 0.00 Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 13 March 28, 2008 (a) Baseline - # of Trips (b) Baseline 3 VMT Figure 2. Hourly distribution of number of trips and vehicle miles traveled of all light- duty vehicles estimated for the South Coast Air Basin of California in the year 2050. Once the overall vehicle activity is obtained, information on vehicle daily mileage is needed to determine the overall daily range of a vehicle. For a given all-electric range of a PHEV, information on daily mileage per vehicle allow calculating the fraction of miles that a PHEV can drive with the electric motor, as well as the fraction of miles for which a PHEV need to use the internal combustion engine. For a scenario that assumes that 100% of light-duty vehicles are PHEVx, being x the all-electric range for that PHEV, the methodology to obtain the total miles under conditions of all-electric charge depleting and charge sustaining modes is as follows: 1. Assume hourly distribution of trips by vehicle and a charging cycle: According to EMFAC, the number of daily trips per vehicle is 6.15. Additionally, the distribution of number of trips can be calculated from adding the hourly frequencies of trips for all mileage ranges presented in Table 4. Assuming one charge per day and the start of the daily activity at 6 am, the cumulative number of trips as a function of time is calculated and presented in Table 5. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 14 March 28, 2008 Table 5. Hourly distribution of trip starts and estimated hourly cumulative number of trips of an average light-duty vehicle assuming the start of daily activity at 6 am. Time of day (hour) 0 1 2 3 4 5 6 7 8 9 10 11 Trip starts (%) 0.8 0.4 0.2 0.2 0.3 0.5 1.9 5.7 5.6 4.7 5.1 7.2 Cumulative number of trips 6.1 6.1 6.1 6.1 6.1 6.2 0.1 0.5 0.8 1.1 1.4 1.9 Time of day (hour) 12 13 14 15 16 17 18 19 20 21 22 23 Trip starts (%) 8.3 6.9 7.4 7.8 7.4 7.9 6.4 5.1 3.4 3 2.1 1.8 Cumulative number of trips 2.4 2.8 3.3 3.7 4.2 4.7 5.1 5.4 5.6 5.8 5.9 6.0 2. Multiply the cumulative number of trips by the average mileage in each mileage bin: This step assumes that every single vehicle drive the same length of a trip daily. For example, a vehicle that starts at 6 am a trip that is 3 miles long will travel 6.2 times the same distance. In reality, vehicles undergo trips of different length during a day. Trips from home to work and the way back can be longer than short trips for grocery shopping. However, there is no available information on connectivity between trips. As a result, this step is a first approximation to determine how many daily trips could accumulate enough miles to go over the all- electric range of a PHEV. Table 6 presents the results of multiplying the values of Table 5 by the average trip length in each VMT range bins. The result is the cumulative mileage per trip length bin and per hour, CMT VMT,h . For the case of PHEV40, vehicles with trips in the 5-10 mile range will exceed the 40-mile range at 7 pm, whereas vehicles with trips in the 25-30 range will exceed the 40-mile range at 11 am. In conclusion, based on this methodology most trips in the morning will be able to operate in all-electric mode and the demand for charge sustaining operation, i.e. use of the internal combustion engine, will increase in the afternoon hours. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 15 March 28, 2008 Table 6. Cumulative mileage per trip length bin, CMT VMT,h , assuming hourly distribution of trips presented in Table 5 Vehicle Miles Travelled (VMT) Range Bins < 1 1 0 5 5 0 10 10 0 15 15 0 20 20 0 25 25 0 30 30 0 35 35 0 40 40 0 45 45 0 50 TIME Average mileage in each VMT range (hour) 0.5 3.0 7.5 12.5 17.5 22.5 27.5 32.5 37.5 42.5 47.5 0 3 18 45 76 106 136 167 197 227 258 288 1 3 18 46 76 107 137 167 198 228 259 289 2 3 18 46 76 107 137 168 198 229 259 290 3 3 18 46 76 107 137 168 199 229 260 290 4 3 18 46 77 107 138 168 199 230 260 291 5 3 18 46 77 108 138 169 200 231 262 292 6 0 0 1 1 2 3 3 4 4 5 6 7 0 1 4 6 8 11 13 15 18 20 22 8 0 2 6 10 14 18 22 27 31 35 39 9 1 3 8 14 19 25 30 36 41 47 53 10 1 4 11 18 25 32 39 46 53 60 67 11 1 6 14 23 33 42 51 60 70 79 88 12 1 7 18 30 42 53 65 77 89 101 113 13 1 8 21 35 49 63 77 91 105 119 133 14 2 10 24 41 57 73 89 106 122 138 154 15 2 11 28 47 65 84 103 121 140 159 177 16 2 13 31 52 73 94 115 136 157 178 199 17 2 14 35 58 82 105 129 152 175 199 222 18 3 15 38 63 89 114 139 165 190 215 241 19 3 16 40 67 94 121 148 175 202 229 256 20 3 17 42 70 98 126 154 182 210 238 266 21 3 17 43 72 101 130 159 188 217 245 274 22 3 18 44 74 103 133 162 192 221 251 280 23 3 18 45 75 105 135 165 195 225 256 286 3. Determine the cumulative mileage in each mileage bin that exceeds x -mile range: The values calculated in the previous step, CMT VMT,h , determine the time of the day that trips in a particular VMT range will require starting the internal combustion engine of PHEV vehicles. If CMV at an hour h in the tripe length range VMT is equal to or larger than the all-electric range x , the number of trips at that ( VMT , h ) coordinate are accounted for the total number of trips that require using the engine. For example, for a PHEV40, the resulting distribution of trips that require using the engine by hour and by VMT range is presented in Table 7. Results show that all trips from 6 am to 8 am are exclusively within the all- electric range. Consequently, there are no emissions associated with the engine at Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 16 March 28, 2008 those particular hours, which implies a significant reduction in emissions from automobiles during the morning commute. Table 7. Distribution of trips that exceed the all-electric range of 40 miles and that require the use of the internal combustion engine Vehicle Miles Travelled (VMT) Range Bins TIME < 1 1 0 5 5 0 10 10 0 15 15 0 20 20 0 25 25 0 30 30 0 35 35 0 40 40 0 45 45 0 50 (hour) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0 0 0 49281 26880 0 4480 22400 13440 0 0 0 1 0 0 49281 4480 4480 0 0 0 0 0 0 2 0 0 26880 13440 0 0 4480 0 0 0 0 3 0 0 22400 13440 0 0 0 0 0 0 0 4 0 0 13440 22400 26880 0 0 0 0 0 0 5 0 0 40320 40320 22400 13440 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 4480 0 0 10 0 0 0 0 0 0 0 13440 4480 0 0 11 0 0 0 0 0 35840 13440 4480 0 0 0 12 0 0 0 0 80641 17920 22400 13440 4480 0 0 13 0 0 0 0 85121 26880 22400 13440 13440 4480 4480 14 0 0 0 170242 85121 62721 26880 4480 17920 0 4480 15 0 0 0 165762 116481 67201 17920 17920 4480 4480 0 16 0 0 0 291203 67201 58241 22400 26880 4480 0 0 17 0 0 0 179202 129921 89601 35840 22400 17920 13440 0 18 0 0 0 165762 44800 76161 13440 13440 0 13440 0 19 0 0 327044 143362 44800 22400 13440 17920 4480 4480 0 20 0 0 286723 116481 26880 13440 26880 0 4480 0 4480 21 0 0 192642 116481 62721 26880 17920 13440 13440 0 0 22 0 0 161282 85121 40320 17920 4480 13440 4480 4480 0 23 0 0 116481 35840 22400 13440 22400 0 13440 0 0 Figure 3 shows the hourly distribution of trips and VMT that require the engine on for scenarios with PHEV8, PHEV20 and PHEV40. Based on the methodology described above, the number of trips and total VMT that require the engine on are significantly lower than the total number of trips and miles travelled by all vehicles, as shown in Figure 2. The number of trips with the engine on decrease dramatically with respect to total number of trips as the all-electric range increases, because a high fraction of trips correspond to short range trips, which in cumulative terms do not exceed the all-electric range. The number of miles travelled with the engine on does not decrease with Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 17 March 28, 2008 increasing the all-electric range as dramatically as the number of trip, because the highest percentage of trips with the engine on corresponds to trips with a long range of VMT. (a) PHEV8 - # of Trips (b) PHEV8 3 VMT (c) PHEV20 - # of Trips (d) PHEV20 3 VMT (e) PHEV40 - # of Trips (f) PHEV40 - VMT Figure 3. Hourly distribution of number of trips and vehicle miles traveled that require the internal combustion engine of PHEVs in four different scenarios: PHEV8, PHEV20, PHEV40 and Baseline Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 18 March 28, 2008 Table 8 presents the percentage of total number of trips and VMT that require the use of the internal combustion engine for four different cases: 1) all light-duty vehicles are PHEV8, 2) all light-duty vehicles are PHEV20, 3) all light-duty vehicles are PHEV40, 4) all light-duty vehicles are EV. As mentioned above, there is a dramatic reduction in the fraction of trips that require the engine 3 from 52.8 % to 11.1 % 3 as the all-electric range increases from 8 to 40 miles. On the other hand, although only 11.1% of the trips would require the use of engine if all light-duty vehicles were PHEV40, these trips correspond to 35.6 % of the total miles traveled. Table 8. Percentage of total trips and total miles that require the use of the internal combustion engine, the total electricity needed to re-charge batteries, and the total power needed using 8-hour and 24-hour re-charging cycles, for four different PHEV cases: PHEV8, PHEV20, PHEV40 and EV Case % Trips with engine on % Miles with engine on Total electricity (GWh) Total power (8 0 hour charging cycle, GW) Total power (24 0 hour charging cycle, GW) PHEV8 52.8 79.6 17.71 2.21 0.74 PHEV20 19.9 51.0 42.55 5.32 1.77 PHEV40 11.1 35.6 55.92 6.99 2.33 EV 0 0 0 0 86.86 10.86 3.62 The widespread use of PHEV presents an opportunity for utility companies to use excess power capacity that is available during off-peak hours. On the other hand, PHEV could significantly increase the peak power demand if these vehicles are re-charged during peak demand hours. Hence, the need for extra power capacity due to widespread use of PHEV will depend strongly on the strategy used and control systems developed for vehicle re-charging. Some studies even suggest that PHEV could be connected to the grid bi-directionally, being able to act as a buffer to provide additional capacity to the grid during peak demand hours and using the grid to re-charge the battery during off-peak hours. This vehicle-to-grid concept could help improve grid stability in the future, although currently there are plentiful challenges that need to be overcome to enable vehicle-to-grid power, including design of the vehicle batteries for more cycling and longer life, controls, interconnection hardware, billing and payment structures, monitoring equipment, utility pricing and rate policies, etc. As a result, a scenario that includes vehicle-to-grid power is not considered herein. Table 8 presents the amount of electricity needed to power the PHEV vehicles as a function of the all-electric range. Note that the PHEV20 scenario implies that nearly half the total daily mileage in the SoCAB will be all-electric. As a result, the PHEV20 scenario would require nearly half the electricity of the case in which all LDA are EV. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 19 March 28, 2008 Doubling the all-electric range from PHEV20 to PHEV40 would increase the all-electric mileage to 65% of total light duty VMT, whereas the PHEV8 case would provide all- electric range for only 20% of the total light duty VMT. Table 8 also presents the capacity of power generation needed to recharge all vehicles using two different charging cycles: (1) all vehicles are charged at night (from 10 pm to 6 am) in an 8-hour charging cycle, and (2) all vehicles are constantly being charged (evenly distributed opportunity charging) during the day. The 8-hour charging cycle requires three times more capacity than the case of a 24-hour charging cycle. However, the power demand for the 8-hour cycle could be absorbed completely by the excess power capacity not used during off- peak power demand hours, whereas the 24-hour cycle could require additional installed capacity for the power demand during periods of peak power demand. In summary, the methodology to establish the demand for all-electric range and for charge-sustaining mode range suggest that early-morning trips and short trips will be able to occur within the all-electric range. Conversely, for trips in the afternoon hours, and especially for long trips, the cumulative daily mileage range will exceed the all-electric range, and hence, will need to use the internal combustion engine. The additional power needed for PHEV will depend on the all-electric range as well as on the charging cycle for the PHEV. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 20 March 28, 2008 4. PRODUCTION OF ELECTRICITY FOR VEHICLES The increase in electricity demand due to widespread commercialization of PHEV and/or EV technologies will add to the currently increasing demand for electricity, which is increasing at a rate of 1.5% per year. Conventional power generation outside of the air basin could be used to meet the increasing demand, although this type of generation is constrained by electricity transmission capacity and resistance to introducing new transmission lines. An alternative that could provide power for the increasing demand is distributed generation. The implementation of DG implies the installation of electricity generators near the place of use. This strategy reduces the transmission losses that conventional electricity from a remote power plant to the end users. In addition, the excess heat from most DG technologies can be used for space heating and air conditioning, and hence, reducing the energy use from a boiler. The cogeneration of electricity and heat is commonly referred as Combined Heating and Power (CHP). The use of CHP improves the overall efficiency of DG and can provide net emission reductions with respect to power generation without heat recuperation. On the other hand, large fraction of central electricity generation is produced outside the air basin in which the power is used, as opposed to DG, which is installed inside the air basin in which the electricity is consumed. As a result, this potential shift from central to distributed power generation may increase pollutant emissions in an air basin and lead to higher levels of ambient ozone and particulate matter concentrations. There are numerous studies that analyzed the potential impacts on pollutant emissions that DG would cause in California (Iannuci et al., 2000; Allison and Lents (2002); Heath et al. (2004)). In addition, Medrano et al. (2008) developed a methodology to create spatially- and temporally-resolved pollutant emissions from DG. Rodriguez et al. (2006) applied that methodology to assess the air quality impacts of DG implementation scenarios in the South Coast Air Basin of California for the year 2010. The methodology considered information from DG market studies, spatial distribution of economic sectors, and emission regulations, among other factors. Rodriguez at al. used a three-dimensional air quality model to assess the impacts of DG on ozone and secondary particulate matter formation, and concluded that realistic implementation of DG technologies would have a marginal effect on air quality by 2010. However, they suggested that increased DG penetration in future years could affect compliance with air quality standards. An ongoing effort by the Advanced Power and Energy Program is considering long- term effects of DG implementation by the year 2030. This study is building upon the work presented by Rodriguez at al. (2006), and uses the methodology described by Medrano et al. (2008) to estimate the future penetration of DG technologies in the SoCAB. The study uses updated information on DG market studies (EPRI, 2005) and updated emissions factors for DG technologies (E2I, 2004). Results suggest that DG implementation will mostly consist in gas turbine and natural gas internal combustion Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 21 March 28, 2008 engines (as shown in Figure 4). However, recent regulations related to the Assembly Bill 32 could for the DG market to adopt cleaner technologies, such as fuel cells, in addition to renewable technologies. 37.4% 59.2% 0.5% 2.2% 0.4% 0.4% LTFC HTFC MTGS NGIC TURB HYBR Figure 4. Distribution of technologies for DG implemented in the SoCAB for the year 2030 (from Samuelsen et al. 2008). LTFC: low-temperature fuel cell; HTFC: high- temperature fuel cell; MTG: micro-turbine generators; NGIC: natural gas internal combustion engines; TURB: gas turbines; HYBR: fuel cell-gas turbine hybrid system This study assumes that DG will be used for in-basin generation of electricity and that DG implementation takes place following the technology mix presented in Figure 4. Using the methodology presented by Medrano et al. (2008), DG units are spread throughout the SoCAB following land use distribution. The resulting emissions from this mix for the all-EVcase, which would require 86.9 GWh of electricity, are presented in Table 9. For sake of comparison, Table 9 presents emissions from DG per total miles traveled by the EV. In comparison with the emission factors for the HEV, the emissions from DG are significantly lower, except for PM emissions. Emissions of NO X and VOC from DG in the EV case are 43% and 81% lower than in the case of all HEV. In addition, start-up emissions from HEV make these differences even bigger. Emissions of PM 2.5 in the EV case are 15% higher if start-up emissions in the HEV are not accounted for. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 22 March 28, 2008 Table 9. Total emissions from distributed generation to produce electricity for a pure electric vehicle fleet in the SoCAB by the year 2050 (in tons per day), emissions from DG per mile, and DG emission factors relative to the HEV emission factors Total emissions (t/d) DG Emission Factor (g/mile) (DG EF) / (HEV EF) VOC 0.308 0.001 0.19 NO X 1.868 0.007 0.57 CO 3.406 0.013 0.12 SO X 0.233 0.001 0.63 PM 2.5 1.885 0.007 1.15 Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 23 March 28, 2008 5. PERSONAL VEHICLE SCENARIOS 5.1 All-electric vehicle scenarios These set of scenarios consists in substituting all light-duty vehicles with all-electric vehicles. Hence, this scenario assumes that in the future, battery technology will be developed enough to allow a substantially long range that will not require additional power by internal combustion engines or other type of propulsion. As a result, emissions from conventional automobiles are removed from the basin. However, production of electricity to power the electric vehicle will introduce new foci of emissions in the basin, unless this electricity is produced by renewable sources, such as photovoltaics or wind power, by nuclear energy, or by any type of generation that is located outside the air basin. To analyze the effect of emissions from electricity generation needed for electric automobiles, two scenarios are developed: (1) All-electric vehicle with no emissions from electricity production (EV): all emissions from light-duty vehicles are removed. No additional emissions are introduced as electricity generation is assumed to be non-emitting or located outside the domain. (2) All-electric vehicle with in-basin electricity production by distributed generation (EVDG): all emissions from light-duty vehicles are removed. Generation of electricity to power the electric vehicles is produced inside the basin by distributed generation, which includes gas turbines, reciprocating engines, and fuel cells. 5.2 All hybrid electric vehicle scenario This scenario consists in substituting all light-duty vehicles with hybrid electric vehicles as described in Section 2.2. This case assumes that the emission factors for all light-duty vehicles correspond to those of a 2000 Toyota Prius. As shown in Section 2, emission factors for the Toyota Prius are significantly smaller than the emission factors for an average LDA estimated by EMFAC. As a result, important emissions reductions with respect to the baseline are obtained in this scenario. Additionally, HEV have better gas mileage than conventional LDA, and could lead to additional emission reductions in the fuel supply chain, as gasoline demand in an all-HEV case could be lower than in the baseline. However, this study does not account for emissions associated to gasoline production. 5.3 All-plug-in hybrid electric vehicle scenarios This set of scenarios consists in substituting all light-duty vehicles with plug-in hybrid electric vehicles. In practical terms, these scenarios are a combination between the all-electric case and the HEV, as there are emissions associated with electricity production, as well as with the operation of the engine. To analyze the effect of the all- Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 24 March 28, 2008 electric range on the resulting emissions, in addition to the effect of electricity production, the following scenarios are developed: (1) All plug-in hybrid electric vehicles (PHEV40) with no emissions from electricity production: all emissions from light-duty vehicles are removed. Emissions associated to HEV are only introduced when the 40-mile all-electric range is exceeded, as described in Section 3. No additional emissions are introduced as electricity generation is assumed to be non-emitting or located outside the domain. (2) All plug-in hybrid electric vehicles with in-basin electricity production (PHEV40DG): all emissions from light-duty vehicles are removed. Emissions associated to HEV are only introduced when the 40-mile all-electric range is exceeded, as described in Section 3. Generation of electricity to power the electric vehicles is produced inside the basin by distributed generation, which includes gas turbines, reciprocating engines, and fuel cells. (3) All plug-in hybrid electric vehicles with in-basin electricity production and no start-up emissions (PHEV40DGnosu): all emissions from light-duty vehicles are removed. Emissions associated to HEV are only introduced when the 40-mile all- electric range is exceeded, as described in Section 3. Generation of electricity to power the electric vehicles is produced inside the basin by distributed generation, which includes gas turbines, reciprocating engines, and fuel cells. Start-up emissions from the operation of the engine when the all-electric range is exhausted are eliminated. Certain control strategies that are under development are aiming to reduce emissions from PHEV by heating the catalyst some time before the battery reaches the minimum state of charge and the internal combustion engine is started. (4) All plug-in hybrid electric vehicles with in-basin electricity production (PHEV20DG): all emissions from light-duty vehicles are removed. Emissions associated to HEV are only introduced when the 20-mile all-electric range is exceeded, as described in Section 3. Generation of electricity to power the electric vehicles is produced inside the basin by distributed generation, which includes gas turbines, reciprocating engines, and fuel cells. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 25 March 28, 2008 6. AIR QUALITY MODEL FORMULATION The University of California, Irvine - California Institute of Technology (UCI-CIT) atmospheric chemical transport model is used to analyze the air quality in the SoCAB. The computational domain corresponds to an irregular region composed of 994 columns of cells (See Figure 5). Each column corresponds to a 5 km by 5 km region in the x, y plane and extends 1100m in height. The columns are partitioned into 5 cells in the z direction. The UCI-CIT model includes the CalTech Atmospheric Chemistry Mechanism (CACM) (Griffin et al., 2002a; Pun et al., 2002; Griffin et al., 2002b). This chemical mechanism is intended for use in three-dimensional urban/regional atmospheric models, with O 3 formation and secondary organics aerosol (SOA) production. CACM includes 191 species and 361 reactions attaining an accurate description of the chemical processes. Figure 5. UCI-CIT Airshed modeling domain of the South Coast Air Basin of California. 6.1 Meteorological Conditions The Southern California Air Quality Study (SCAQS) was a comprehensive campaign of atmospheric measurements that took place in the SoCAB, during August 27- 29, 1987. The study collected an extensive set of meteorological and air quality data that has been used widely to validate air quality models (Meng et al., 1998; Griffin et al., 2002a; Pun et al., 2002; Griffin et al., 2002b, Moya et al., 2002; Knipping and Dabdub, 2002). Zeldin et al. (1990) found that August 28, 1987 is representative of the meteorological conditions in the SoCAB, which makes it suitable for modeling. In addition, the August 27-28, 1987 episode is statistically within the top 10% of severe ozone-forming meteorological conditions. Hence, meteorological conditions for August 28 are used here as the basis to evaluate the effects of changes in vehicle emissions. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 26 March 28, 2008 The SCAQS episode in August 27-29, 1987 was characterized by a weak onshore pressure gradient and warming temperatures aloft. The wind flow was characterized by a sea breeze during the day and a weak land-mountain breeze at night. The presence of a well-defined diurnal inversion layer at the top of neutral and unstable layers near the surface, along with a slightly stable nocturnal boundary layer, facilitated the accumulation of pollutants over the SoCAB, which lead to high ozone concentration occurrence. 6.2 Baseline Emissions Currently, there are no emission estimates available beyond 2023. Only EMFAC, a model used to generate on-road mobile emissions, is capable of estimating emissions for years up to 2040. The EMFAC model is developed by the ARB, and uses information on vehicle activity from the Department of Motor Vehicles and the California Transportation Department. The total emissions from vehicles can then be calculated using emission factors derived from vehicle testing. These emission factors depend on the number of starts, the ambient conditions and the speed of the vehicle, among other factors. Results from the EMFAC model provide emissions from vehicle operation, as well as evaporative emissions of VOC, and particle emissions from braking and tire wear (ARB, 2007). Figure 1 shows the relative change in vehicular activity, emissions from on-road mobile sources and fuel use for the period 2010-2040. Although the number of vehicles, trips and vehicle miles traveled are estimated to increase, emissions of criteria pollutants are expected to decrease due to reduction of vehicle tailpipe emissions. This reduction is caused by the progressive market penetration of low-emitting vehicles, and the gradual retirement of higher-emitting older models. Emission source apportionment for the 2023 inventory is presented in Table 10. Emissions from on-road mobile sources account for 24%, 40% and 36% of the total ROG, CO and NO X , respectively, in the emission inventory estimated by ARB for the year 2023. Assuming that emissions from all the sources except on-road mobile sources stay constant, emissions for up to the year 2050 may be estimated by extrapolating the emission reductions to the mobile sources, as shown in Figure 1. As a result, baseline emissions of ROG, NO X and CO for the year 2050 decrease to 373 tpd, 94 tpd and 1522 tpd, respectively, whereas PM 2.5 emissions increase to 92 tpd. Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 27 March 28, 2008 Table 10. Source apportionment of the 2023 emissions inventory for the South Coast Air Basin of California Emissions by major source % with respect to total emissions in 2023 2023 Emissions Stationary Sources Petroleum Production Off-Road Vehicles On-Road Vehicles (t/d) VOC 44.7 6.5 25.2 23.6 420 NO X 14.4 0.0 50.0 35.6 114 CO 6.1 0.3 53.2 40.4 1966 SO X 16.8 2.1 78.9 2.1 19 PM 2.5 67.6 1.0 17.6 13.7 88 Table 11. Source apportionment of the 2050 emissions inventory for the South Coast Air Basin of California, using 2023 emissions inventory and extrapolating on-road emissions using EMFAC estimates Emissions by major source % with respect to total emissions in 2050 2050 Emissions Stationary Sources Petroleum Production Off-Road Vehicles On-Road Vehicles (t/d) VOC 50.3 7.3 28.3 14.1 373 NO X 17.4 0.0 60.3 22.3 94 CO 7.9 0.4 68.7 23.0 1522 SO X 13.4 1.7 62.9 22.0 24 PM 2.5 64.8 1.0 16.9 17.4 92 Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 28 March 28, 2008 7. AIR QUALITY IMPACTS OF VEHICLE SCENARIOS 7.1 Baseline air quality The synoptic conditions in the SoCAB create a regime of circulation that favors transport of pollutants, emitted mainly in Los Angeles and Long Beach, towards the north east. In the northeastern part of the domain there are mountain ranges that trap the pollution arriving from upwind, leading to accumulation of ozone. Near Riverside, a high density of dairy farms produces ammonia, which reacts with nitric acid formed via oxidation of nitrogen oxides emitted upwind. Nitric acid and ammonia react to form secondary particulate matter leading to the high PM 2.5 near Riverside. Two other foci of PM 2.5 concentration develop near Central Los Angeles and the port of Long Beach. The former is due to direct emissions from vehicles, whereas the latter comes from the activity at the port, where there are high emissions from trucks and ships. Although baseline simulations for the year 2050 are based upon emission inventories for 2023 that have been developed for the 2007 AQMP to demonstrate attainment of ozone and PM 2.5 air quality standards, ozone and PM 2.5 concentrations exceed the established air quality standards (84ppb ozone; 50 ¼ g/m 3 PM 2.5 ) as shown in Table 12. Jimenez et al. (2003) and Carreras-Sospedra et al. (2006) suggest that the CACM chemical mechanism predicts higher oxidative capacity that leads to higher concentrations of O 3 than those predicted by other chemical mechanisms, such as SAPRC-99, which was used to produce the results in the AQMP. Nonetheless, simulation results by UCI-CIT model using CACM agree reasonably well with observations (Griffin et al. 2002a). Table 12. Maximum concentration of pollutants for the 2050 baseline case and California Ambient Air Quality Standards (CAAQS) Pollutant Year 2050 CAAQS 1-hour O 3 139 ppb 90 ppb 8-hour O 3 118 ppb 70 ppb 1-hour CO 1.3 ppm 20 ppm 1-hour NO 2 69 ppb 180 ppb 24-hour PM 2.5 66 ¼ g/m 3 35 ¼ g/m 3 Air Quality Impacts of Some Alternative Vehicle Options UC Irvine National Fuel Cell Research Center 29 March 28, 2008 (a) (b) Figure 6. Baseline pollutant concentrations in the year 2050 in the South Coast Air Basin of California: (a) peak ozone concentrations, (b) 24-hour average PM 2.5 concentrations 7.2 Impacts of vehicle scenarios on pollutant emissions The impacts of the vehicle scenarios presented in Section 5 on basin-wide emissions are analyzed in this section. The differences in emissions due to the implementation of each scenario can be analyzed with respect to baseline light-duty emissions (see Figure 7) and with respect to total baseline emissions (see Figure 8). As shown in Figure 7, all scenarios lead to decreases in emissions with respect to baseline light-duty vehicle emissions of 50% or higher. Note that the all EV scenario implies the total elimination of tail-pipe emissions from light-duty vehicles and represents the case with the lowest emissions. On the other end, the all HEV scenario represents the case with the highest emissions. In the case of all-EV with emissions from electricity production through DG, total emissions are lower than in the case of all-HEV, suggesting that EV can potentially reduce emissions further than any hybrid-ICE strategy, even if emissions from electricity production are included. Results show that use of PHEV will reduce emissions with respect to using HEV, even if emissions from electricity production are accounted for. Increasing the all-electric range reduces the total emissions from automobiles, except for PM emissions because per-mile PM emissions from DG are slightly higher than from HEV (as shown in Table 9). Removing start-up emissions from the PHEV40 case reduces by 2% further the total emissions from light- duty vehicles, with respect to conventional LDA emissions. Overall, the scenarios with alternative vehicle technologies could reduce total basin- wide emissions. Total basin-wide emissions of NO X and CO could decrease by up to 10%, whereas VOC, SO X and PM emissions could decrease by up to 5%, with respect to baseline 2050 emissions. These are moderate decreases that could be augmented if hybrid or battery-electric technologies are implemented in vehicles of higher sizes. Although light-duty vehicles contribute with nearly half of the total VMT, vehicles

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