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Chapter 7 Traffic and Air Quality

Chapter 7 Traffic and Air Quality. Workgroup Meeting to Discuss “Weekend Effect” Research April 13, 2000 L. C. Larsen. Traffic and Air Quality. Section 7.1 Weigh-in-Motion data analysis Section 7.2 Freeway “loop counter” data analysis Section 7.3

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Chapter 7 Traffic and Air Quality

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  1. Chapter 7Traffic and Air Quality Workgroup Meeting to Discuss “Weekend Effect” Research April 13, 2000 L. C. Larsen

  2. Traffic and Air Quality • Section 7.1 • Weigh-in-Motion data analysis • Section 7.2 • Freeway “loop counter” data analysis • Section 7.3 • Comparisons of traffic and air quality profiles

  3. Section 7.1WIM Data Analysis • 12 Stations relevant to the SCAB • Freeways only (no surface streets) • Daily (24-hour) total counts • Hourly data not yet obtained • Separate counts for 14 vehicle classes • Summarized as • Heavy-duty trucks (classes 8-14) • Non-heavy-duty vehicles (classes 1-7)

  4. Section 7.1WIM Data Analysis • Stations grouped as • “Central” • “Peripheral” • Results • Systematic and substantial DOW differences • HDT drop much more than LDV on WE • HDT drop greater in “central” vs “peripheral”

  5. Section 7.2Fwy Loop-Count Data Analysis • Los Angeles and Orange Counties only • Freeways only (no surface streets) • 11 sub-regions or domains • Several domains have WIM station • All domains have related AQ monitor • Hourly counts of total vehicles • No separation by WIM vehicle classifications • By day-of-week

  6. Section 7.2Fwy Data Analysis Domains 1. Anaheim 7. Lynwood 2. Azusa 8. N. Long Beach 3. Burbank 9. Pico Rivera 4. Hawthorne 10. Pomona 5. Irvine (El Toro) 11. Reseda 6. L.A. CBD (N. Main)

  7. Section 7.2Fwy Loop-Count Data Analysis • Tables and graphs in current draft • tables to go in appendix later • Summaries maintain “balance” for both sides of a freeway • Thorough QC steps performed • High accuracy and precision (within < 5%)

  8. Section 7.2Fwy Loop-Count Data Analysis • Results • Substantial day-of-week differences in the hourly profiles • Large differences in total volume and timing • Total - Saturday (-11%) and Sunday (-22%) • Daylight - Saturday (-17%) and Sunday (-30%) • 6-8 a.m. - Saturday (-52%) and Sunday (-73%) • The 11 domains are more similar than different • Differences are mostly in afternoon traffic

  9. Section 7.3 Compare profiles for traffic/AQ • Comparisons highlight hypotheses • Compare daily summaries • overall ups and downs • Compare hourly summaries • lag between traffic and AQ • Compare parts of the day • daylight hours

  10. Section 7.3 Compare profiles for traffic/AQ • Comparisons based on DOW profiles with hourly values expressed as proportions with respect to mid-week levels • both traffic and pollutants • all domains viewed on similar scale

  11. Section 7.3 Compare profiles for traffic/AQ • Comparisons of pollutants with expected changes due to traffic behavior by day-of-week • CO : LDV and HDT • NOx : LDV and HDT • VOC/NOx on WE vs WD using AQ • CO behavior as surrogate for VOC behavior • VOC/NOx on WE vs WD using EMFAC* • WIM factors applied for all hours by DOW * EMFAC 2000 Version 1.99

  12. Section 7.3 Compare profiles for traffic/AQ • Strong correspondence between traffic activity and air quality • Not a perfect match • Both daily totals and timing are related • Crucial data gaps • Hourly resolution for vehicle classes • Surface street data • Hourly • Vehicle classification

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