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Introduction to RTC Engine Starts Project

Introduction to RTC Engine Starts Project. Background. Clark County moderate non-attainment carbon monoxide (CO) and ozone Effective control measures and accurate modeling require identification and quantification of CO and hydrocarbon sources – emissions inventory

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Introduction to RTC Engine Starts Project

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  1. Introduction toRTC Engine Starts Project

  2. Background • Clark County moderate non-attainment carbon monoxide (CO) and ozone • Effective control measures and accurate modeling require identification and quantification of CO and hydrocarbon sources – emissions inventory • Mobile sources significant emitters • Cold start engines contribute significant portion of emissions • Mobile 6.2 emissions model uses default temporal distribution of cold engine starts based on limited data from early 1990’s

  3. More background • Current EPA Mobile 6.2 default data for engine starts largely based on: • Two studies in early 1990’s for Baltimore, MD and Spokane, WA • Total sample size: about 130 cars. Average 7.2 starts/day • A portion of computed Mobile 6.2 emissions estimated from number of cold starts • Need valid local data to change from default values • Purpose of this study is to obtain that data!

  4. Goals and Benefits • Goal - Develop local data for temporal distribution of cold and warm engine starts • Anticipated Benefits • Local data input to Mobile 6.2 – more accurate (hopefully lower!) start emissions • Identify major categories of mobile source emissions to be emphasized for controls • Identify short trip proportion – if high, try to remediate through public education • better public awareness of contribution of engine starts to overall emissions

  5. Study Tasks 1. Literature review 2. Identify data collection procedures Demographic classifications and geographic distribution of residents Proportional representation of vehicle categories 3. Conduct pilot study of starts – mid Oct ’04 – 20 Sensors - & survey to identify participants 4. Conduct main study – 100 Sensors – Nov Dec ’04 5. Compile data and analyze 6. Write and submit report and present results 7. Target completion date 1-31-05

  6. Data acquisition technology • GeoStats On/Off data Logger plugs into 12V outlet – size of deck of cards (please see photo, next page) • Detects voltage fluctuation when engine starts or stops • Records events as “ON” or “OFF” as day, hour:min:sec • Software computes length of time between (ON and OFF) or (OFF and ON) • Device does NOT track location or destination of vehicle

  7. GeoStats sensor & Y-cable

  8. Where the sensor goes – 12v power tap/cigarette lighter 12v tap

  9. Typical sensor data file

  10. Goals for pilot study • Scope: about 20 sensors in the field for two weeks • Work out • Contact logistics • Transportation logistics of deploying and retrieving sensors to drivers’ homes • Data download and archiving methods • Dates: October 12-25

  11. Goals for full study • Scope: 100 sensors in field for 8 weeks– 800 data sets (hold another 20 in reserve to replace loss/damage) • Eight (8) cycles of pick up and drop off deployment • Capture representative cross section of drivers – major employment and life style categories • Proposed dates: November 1 – December 27

  12. How sensors deployed • Participants identified through RTC and Cannon Center Surveys • UNLV telephones to schedule sensor installation • UNLV arrives at residence to install sensor, record install date/time, mileage, arrange pick up time one week later • Driver operates car for a week with sensor installed • Driver or UNLV removes sensor from car, records removal date/time, mileage • UNLV returns to pick up sensor

  13. How participants’ privacy will be respected • Individual starts/stops NOT reported by name or address in any publication • Destinations of trips not recorded • Names, occupations, marital status, ethnicity, and addresses, collected by permission only • will be recorded and used to ensure sensors are distributed in a way that fairly represents the metro area population • will kept in a secure database by UNLV and will not be distributed to anyone for any reason

  14. What will be done with sensor data • Analyze combined sensor data files to estimate: • Average # of starts or stops per weekday or weekend day) (eg. 7.2 starts/weekday, & 5.4 starts/weekend day) • Individual start sensor record may be shown as example data, but will be anonymous (see plot next slide) • Frequency of starts/stops/soaks throughout the day by hour – typical plot Figure 7

  15. Types of information produced • “Cold” start; engine off more than 8 hours before start • “Warm” start, engine off less than 8 hours • “Hot” soak, engine on > 20 minutes followed by engine off < 1 hour

  16. Thank you! Our contact info Contact information: David E. James, PhD, PE Associate Professor Phone: 702-895-1067 Fax: 702-895-4401 Email: daveearl@ce.unlv.edu Srinivas Pulugurtha, PhD Assistant Director, Transportation Research Center Civil and Environmental Engineering Phone; 702-895-1362 Fax: 702-895-4401 Email: pss@egr.unlv.edu Vinod Vasudevan, MS Transportation Systems Analyst Transportation Research Center Phone: 702-895-1594 Fax: 702-895-4401 Email: vinodv@egr.unlv.edu

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