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Implications of Electric Bicycle Use in China: Analysis of Costs and Benefits
Volvo Center Workshop-Berkeley7/24/2006Track 1
Christopher R. CherryPhD CandidateInstitute of Transportation StudiesDepartment of Civil and Environmental EngineeringUniversity of California, Berkeley
Partnership with: Pan Haixiao-Tongji UniversityXiong Jian-Kunming University of Science and TechnologyYang Xinmiao-Tsinghua University
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Outline
• Brief Introduction
• Research Question
• Approach and Methodology
• Data
• Conclusion/Expected Results
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Emergence of Electric Two-Wheelers in large Chinese Cities
• Most large Chinese cities have banned or heavily restricted gasoline motorcycles in the city center. In response, electric bicycles and motorcycles that can ride in the bike lane have gained popularity and mode share.
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Personal Cars
Bicycle style electric bike (BSEB)
Scooter style electric bike (SSEB)Sources: Jamerson (2004) LuYuan Electric Bike Company (2006), Yu (2004), China Statistical Yearbook (2005)
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Emergence of Electric Bicycles in large Chinese Cities
• These bikes are regulated by speed and size by the central government
• What are the effects of these bikes on the transportation system?– Environmental implications
• Energy use and emissions– -Production and Use
• Hazardous Waste-Lead Acid Batteries
– Safety of electric bikes and others in lanes– Increased mobility and accessibility
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Research Question
• Do electric bikes provide greater relative benefits in terms of mobility than environmental costs compared to alternative modes?– Energy– Environment– Safety– Mobility
• Compared to what modes? Bus and Bike
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Research Approach• Quantify the costs and benefits of electric bicycle and compare to
standard bicycle and bus to inform appropriate policy on regulation. Case Study of Kunming (3M) and Shanghai (14+M)
Environmental Emissions•Production, Use
Lead Emissions
Safety Impacts
Mortality Morbidity
Mobility changes
Costs
Benefits
Quantify Benefits
In terms of increased Accessibility
City Level Data
Electricity Mix
Mode Split
Average Speed by Mode
Energy Use•Production, Use
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Environmental Impacts-Production
• Production Energy Use and Emissions
– Raw Materials – Assembly Processes– Assumes 5 batteries
over lifespan, and 3 sets of tires (10 year lifespan)
– Note: does not (yet) include solid waste from disposal or energy/pollution impacts of non-ferrous metal mining, glass or battery acid manufacturing
Weight of Electric Bike Materials
BSEB SSEB
Total Steel 18.15 46.1% 26.18 46.5%
Total Plastic 5.67 14.4% 15.22 27.0%
Total Lead 10.28 26.1% 14.70 26.1%
Total Fluid 2.94 7.5% 4.20 7.5%
Total Copper 2.55 6.5% 3.46 6.1%
Total Rubber 1.14 2.9% 1.22 2.2%
Total Aluminum 0.52 1.3% 0.58 1.0%
Total Glass 0.00 0.0% 0.16 0.3%
Total Weight 41.25 65.73
Associated Energy and Emissions of Manufacturing Processes
Energy Use (tonne SCE) 0.061 0.077
Air Pollution (SO2) (g) 131 141
Air Pollution (PM) (g) 84 89
Greenhouse Gas (CO2eq)
Waste Water (kg) 206 222
Solid Waste (kg) 378 493 Sources: China statistical yearbook (2004, 2005), China industrial yearbook (2004), China Data Online, Mao et al. (2006), Price et al. (2001)
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Environmental Impacts-Use • E-bike Energy Use
– For example: 350W motor, 48V/14 Ah battery, 50km range
– Current=Power/Voltage=350W/48V≈7.3 A– Drain Time=14Ah/7.3A=1.9 hours– Energy=Power*Time=350W*1.9h=670Wh=0.67kWh– Energy/Distance=0.67Wh/50km=0.13Wh/km
=1.3kWh/100km– 6.6% electricity transmission loss (national average)– 50,000 km life=695kWh=0.085 tonne SCE
• Emissions from Electricity Production– Kunming1: 52% hydro, 48% coal– Shanghai: 2% hydro, 98% coal– All China: 15% hydro, 75% coal, 8%gas, 2%nuclear
1. China Statistical Yearbook 2005, Energy Foundation China 2005
Electric bike Emissions (g/km)
Kunming Shanghai
SO2 0.066 0.137
NOX 0.015 0.031
PM 0.0033 0.007
Carbons 6.105 12.808
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Environmental Impacts-Lead
• Battery Pollution– 95% of electric bikes use lead acid batteries – Lead batteries last about 300 recharges or 1-2 years (10,000 km)– China Lead Acid Battery Recycling/Loss Rates1
• 4.8% Loss Rate During Manufacture• 27.5% Loss Rate During Mining, Smeltering and Recycling• 62% Recycling Rate
– 36V (10.3kg), 48V (14.7kg) lead content– 36V-3.214 kg lost during manufacture, 3.914 kg lost due to low recycle rate– 48V-4.689 kg lost during manufacture, 5.586 kg lost due to low recycling rate
• Electric bikes indirectly emit 712-1028mg/km into environment!• If 100% recycled, still 321-469mg/km into environment
– For Sake of Comparison-in the USA: • 4% loss from virgin production, 2% from recycling and 1% from manufacturing• A 7.9L/100km (30mpg) car running on leaded fuel emits 33mg/km
1Mao et al. (2006) 2Lave et al.(1995)
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Safety Impacts • One of the issues cited for regulation
– China Bicycle Association1
• Crash Rate is 0.17% for E-Bike (crashes/veh pop)• Crash Rate is 1.6% for cars
– Kunming• 2005-171,000 ebikes2 -98 crashes, 102 injuries, 5 fatalities3
– 0.05% crash rate
– 2400 vkt/year (survey data)
– 0.012 fatalities/1,000,000 vkt
– Zhejiang province 2004
Fatalities4 Injuries4 Veh pop5 Vkt/yr6 Fatality Rate
(fatalities/m- vkt) Motor vehicle 3731 29884 1.81m 18100m 0.206 Bicycle 1194 7148 24.9m 53012m 0.023 Electric bike 129 1660 1.5m 3255m 0.036
1 Ribet (2005), 2 Kunming Public Security Bureau-Vehicle Registration Division, 3 Kunming Public Security Bureau-Traffic Safety Division, 4 Secondary source Zhejiang Public Security Bureau, Zhejiang Bicycle Association, 5 Zhejiang and China Statistical Yearbooks 2005
6 10,000 vkt/year/veh assumed for motor vehicles, average of Kunming and Shanghai survey data for bicycle and e-bike used for two-wheelers
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Mobility
• Mobility can be defined in terms of speed– Measure operating speed of electric motorcycle and compare to other
modes• Floating vehicle studies• Travel time savings can be calculated using value of time methodology • We can also use mobility as a proxy for accessibility
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GPS Travel Time Study
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GPS Travel Time Study-Kunming
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Speed Distribution PDFPDF of Speeds in Shanghai
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PDF of Speeds in Kunming
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Speed km/hr
electric bike
bicycle
10.912.8 14.7 17.9
40%↑
35%↑
From Secondary Data• Average Bus Speed1,2
– Kunming-16km/hr
– Shanghai-<20km/hr
Kunming University of Science and Technology (2005), Shanghai transit agency
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Mobility to Accessibility • Mobility can be defined in
terms of speed, but accessibility is measured in the number of opportunities reached in a specific amount of travel time– Given land use data and
average travel speed on links, accessibility differences can be identified
Image source: Cervero (2005)
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Survey of Two Wheeler Users
• Travel Survey in Shanghai and Kunming– In order to calculate the difference in transportation costs and
benefits, mode shift and vehicle use characteristics must be identified.
• Travel Diary of previous day (Tuesday through Thursday)• How many trips are made per day• What is the average vehicle-kilometer-traveled per day/week/year• Determine alternative mode if e-bike was not available• Demographics of users• Identify travel time and distance of all modes and trips• Can compare time savings if alternative modes were taken
– Survey Bicycle Users, Electric Bike Users and LPG scooter (Shanghai)
– overall sample size 1200
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Preliminary Descriptive Statistics
Shanghai Kunming
Bike E-bike LPG Bike Ebike
Number of trips 1.98 1.94 2.01 2.23 2.53
Trip Length (km) 4.29 4.84 6.65 3.37 3.62
Weekday VKT 8.51 9.41 13.33 7.51 9.16
Average VKT for Environmental Analysis and Mobility Valuation
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Descriptive Statistics Stated Mode Preference for Comparative Environmental Analysis
What Mode Would You Take Otherwise?
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shanghai bike
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Descriptive Statistics
Why Did You Choose This Mode?
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Most People Indicate that they choose e-bike because of speed, but don’t travel (much) farther.
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Why Do We Care?• We tolerate environmental externalities only
because of improved mobility!• Research Approach:
– Costs: increased emissions, battery pollution, and safety– Benefit: reduced travel time/improved accessibility– Case Study of Kunming and Shanghai
• Policy Implication:– Rather than ban electric bikes-accurately price
externalities• Lead battery tax=“pull” incentive to develop better lead battery or
levels the “economic playing field” of NiMH or Li batteries• Clean up lead industry
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Conclusion and Expected Results
• Policy decisions being made on perceived costs of electric bikes
• This research: – Provides a framework to analyze a new mode in this context– Identifies use characteristics of this new, influential mode– Classifies costs that can be priced– I expect that this mode will outperform most other modes (except
perhaps a bicycle) in terms of low externalities and high mobility gains, with the exception of lead emissions
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Still Ahead
• Public Health Impact Analysis of Power Plant Emissions
• Thorough Analysis of Survey Data– Trip Length and Frequency by Purpose– Mode Choice Modeling?
• Identification of Use/Environmental Characteristics of Bus and Bike Modes for comparative analysis
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Questions?Working Papers/Conferences:
Weinert, J., C. Cherry, Z.D. Ma. An Analysis of Key Factors for the Rapid Growth of Electric Bikes in China. EVS22-The 22nd International Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exhibition. Yokohama, Japan. October 23-28, 2006
Cherry, C., J. Weinert, Z.D. Ma. The Environmental Impacts of Electric Bikes in China. TRB?
Cherry, C. The Costs and Benefits of Electric Bike Use in China. WCTRS 2007.
Chris Cherry
www.ce.berkeley.edu/~cherry
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Supplemental Slides
1Maramba et al (2003), 2Suplido et al (2000), 3 US EPA (1997) 4Wang et al (2006)
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Environmental Impacts
• Health Impacts of Lead– WHO/CDC Lead Blood Concentration Guidelines
• Men 40 μg/dL, Women 30 μg/dL, Children 10 μg/dL• Population near recycling plant1
– +20% for adults, +30% for children
• Workers and families of battery maintenance and recycling2
– +330% for adults, +400% for children
– First order approximation of fiscal impact would be costs of hospitalization• 23% of individuals near recycling plant have history of hospitalization vs. 4%
of control• US EPA3 Quantify Health Effects of increased blood lead levels
1Maramba et al (2003), 2Suplido et al (2000), 3 US EPA (1997) 4Wang et al (2006)
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Environmental Impacts • Converting Emissions into Intake
– Intake Fraction-A methodology to calculate exposure• The fraction of pollutants emitted that people eventually inhale-unitless
• iF=f(mass emitted, population, breathing rate, concentration)
• Map concentrations to populations using emissions modeling
• CALPUFF dispersion model calibrated and used in Chinese context1,2,3
• From dispersion models, regression analysis was performed and iF calculated as a function of population distribution and climatic conditions at a power plant
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SO2 SOX NOX PM1 PM3 PM7 PM13
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1.80E-06
1Li et al (2003), 2Zhou et al (2003), 3Zhou et al (2004)
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Impact area of Qujing Power Plant
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Environmental Impacts
• Converting Intake into Public Health EffectsIntake Fraction concentration changes mortality and morbidity rates
– Concentration Response ΔC=C(ebΔP-1)
b=ln(relative risk)/(change in pollutant)
Relative Risk Factor (X% increase in mortality per μ/m3 concentration increase)
1Xu et al (1995) 2Brajer et al (2003)
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Descriptive Statistics
Trip Purpose
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