Implications of Electric Bicycle Use in China: Analysis of Costs and Benefits Volvo Center Workshop-Berkeley 7/24/2006 Track 1 Christopher R. Cherry PhD Candidate Institute of Transportation Studies Department of Civil and Environmental Engineering University of California, Berkeley Partnership with: Pan Haixiao-Tongji University Xiong Jian-Kunming University of Science and Technology Yang Xinmiao-Tsinghua University

Outline Brief Introduction Research Question Approach and Methodology Data Conclusion/Expected Results

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. Bicycle style electric bike (BSEB) Scooter style electric bike (SSEB) Sources: Jamerson (2004) LuYuan Electric Bike Company (2006), Yu (2004), China Statistical Yearbook (2005)

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

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

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

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 % % Total Plastic % % Total Lead % % Total Fluid % % Total Copper % % Total Rubber % % Total Aluminum % % Total Glass % % Total Weight Associated Energy and Emissions of Manufacturing Processes Energy Use (tonne SCE) Air Pollution (SO2) (g) Air Pollution (PM) (g)84 89 Greenhouse Gas (CO2eq) Waste Water (kg) Solid Waste (kg) Sources: China statistical yearbook (2004, 2005), China industrial yearbook (2004), China Data Online, Mao et al. (2006), Price et al. (2001)

Environmental Impacts-Use E-bike Energy Use –For example: 350W motor, 48V/14 Ah battery, 50km range –Current=Power/Voltage=350W/48V7.3 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 –Kunming 1 : 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) KunmingShanghai SO NO X PM Carbons

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 Rates 1 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 kg lost during manufacture, kg lost due to low recycle rate –48V kg lost during manufacture, kg lost due to low recycling rate Electric bikes indirectly emit mg/km into environment! If 100% recycled, still mg/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 1 Mao et al. (2006) 2 Lave et al.(1995)

Safety Impacts One of the issues cited for regulation –China Bicycle Association 1 Crash Rate is 0.17% for E-Bike (crashes/veh pop) Crash Rate is 1.6% for cars –Kunming ,000 ebikes crashes, 102 injuries, 5 fatalities 3 –0.05% crash rate –2400 vkt/year (survey data) –0.012 fatalities/1,000,000 vkt –Zhejiang province 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 ,000 vkt/year/veh assumed for motor vehicles, average of Kunming and Shanghai survey data for bicycle and e-bike used for two-wheelers

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

GPS Travel Time Study

GPS Travel Time Study-Kunming

Speed Distribution PDF From Secondary Data Average Bus Speed 1,2 –Kunming-16km/hr –Shanghai-<20km/hr Kunming University of Science and Technology (2005), Shanghai transit agency

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)

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

Preliminary Descriptive Statistics ShanghaiKunming BikeE-bikeLPGBikeEbike Number of trips Trip Length (km) Weekday VKT Average VKT for Environmental Analysis and Mobility Valuation

Descriptive Statistics Stated Mode Preference for Comparative Environmental Analysis

Descriptive Statistics Most People Indicate that they choose e-bike because of speed, but dont travel (much) farther.

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

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

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

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 22 nd 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 Chris Cherry

Supplemental Slides 1 Maramba et al (2003), 2 Suplido et al (2000), 3 US EPA (1997) 4 Wang et al (2006)

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 plant 1 –+20% for adults, +30% for children Workers and families of battery maintenance and recycling 2 –+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 EPA 3 Quantify Health Effects of increased blood lead levels 1 Maramba et al (2003), 2 Suplido et al (2000), 3 US EPA (1997) 4 Wang et al (2006)

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 context 1,2,3 From dispersion models, regression analysis was performed and iF calculated as a function of population distribution and climatic conditions at a power plant SO 2 SO X NO X PM 1 PM 3 PM 7 PM E E E E E E E Li et al (2003), 2 Zhou et al (2003), 3 Zhou et al (2004)

Impact area of Qujing Power Plant

Environmental Impacts Converting Intake into Public Health Effects Intake Fraction concentration changes mortality and morbidity rates –Concentration Response ΔC=C(e bΔP -1) b=ln(relative risk)/(change in pollutant) Relative Risk Factor (X% increase in mortality per μ/m 3 concentration increase) 1 Xu et al (1995) 2 Brajer et al (2003)

Descriptive Statistics