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Document Sample
Collection and Analysis of
Weekend/Weekday Emissions
Activity Data in the
South Coast Air Basin
Presented by
Dana Coe Sullivan and Lyle R. Chinkin
Sonoma Technology, Inc.
Petaluma, CA
Presented at the
Chairman's Air Pollution Seminar Series
California Air Resources Board
Sacramento, CA
June 30, 2004
What is the Weekend Effect?
Emissions of ozone precursors tend to be
lower on weekends (WE) than on weekdays
(WD).
However, in many cities, WE ozone
concentrations now tend to be equal to or
higher than WD concentrations.
This paradox—the weekend effect—appears
to be growing more common and spreading
geographically over time.
2
The Weekend Effect in Los Angeles
Los Angeles ozone air quality
improved from 1980 to 1999.
– Number of 1-hr exceedances
decreased from about 150 to
only 50 per year.
WE peaks = WD peaks.
– From 1980-1999, WD-WE
difference became more
pronounced.
Source of figure: Austin, J.; Tran, H. “A Characterization of the Weekend-Weekday Behavior of
Ambient Ozone Concentrations in California.” Draft staff report prepared by the Technical Support
and Planning Division, California Air Resources Board, Sacramento, CA, 1999.
3
Purpose and Objectives
Purpose: Address a lack of WE-specific
emissions data, which are needed to
support air quality modeling exercises
for WE conditions in Los Angeles.
Objective: Characterize WD-WE activity
patterns for a variety of emissions
sources in Los Angeles.
4
Importance of On-Road Mobile Sources
2003 SoCAB Emissions (tons per day)
1,200
Natural Sources
1,000 Other Mobile Sources
Other
Mobile On-Road Motor Vehicles
Sources
800 Other Area: Miscellaneous Processes
Mobile
Sources Area: Solvent Evaporation
600
On-Road Point: Industrial Processes
Motor On-Road
Vehicles Motor Point: Petroleum Production And Marketing
400 Vehicles
Point: Cleaning And Surface Coatings
200 Point: Waste Disposal
Point: Fuel Combustion
-
Source: ARB, 2004
ROG NOx http://www.arb.ca.gov/emisinv/emsmain/emsmain.htm
5
Brief Overview – Methods
• Apply an array of methods (e.g., surveys,
in-vehicle instruments, etc.) to directly
measure activities for a variety of emissions
source types.
– On-road mobile sources
– Non-road mobile sources
– Area sources
– Major point sources
• Direct the majority (80%) of effort and
resources to on-road mobile sources.
6
Brief Overview – Findings
• Traffic activities follow predictable weekly patterns.
– Vehicle-miles traveled (VMT)
– Frequencies of soaks or trips
– Speed distributions
– Types of roads driven
– Fleet distributions (heavy-duty versus light-duty)
• Some residential activities—especially recreational
activities—tend to increase on WEs.
• Business-related activities and emissions from
major point sources tend to decline dramatically
on WEs.
7
Presentation Overview
• Data Collection Methods and
Highlights of Findings
– Telephone and mail surveys
– Instrumented vehicle study
– Surface-street traffic counters
– Caltrans weigh-in-motion (WIM) traffic volumes for
freeways
– Continuous emissions monitoring systems (CEMS) data
for major point sources
– Special studies of neighborhoods near air quality
monitoring sites
• Recommendations
• Closing Remarks and Acknowledgments
8
Telephone and Mail Surveys
9
Survey Participation
• Participants were recruited randomly
throughout the SoCAB or from specific,
targeted neighborhoods.
• Results for the randomly selected groups and the
targeted neighborhoods were comparable.
• Compared to past experience, refusal rates were
typical or low for residential and businesses
surveys.
• All participants completed telephone
questionnaires; some completed daily
activity diaries by mail.
10
Daily Activity Diaries
11
Survey Participation
No. Respondents
Daily
Telephone Activity
Refusal
Group Areas Survey Diaries Rate
Targeted
Households
and random 870 488 41%
Small
businesses
Targeted 137 n/a 14%
Construction
businesses
Random 258 n/a 25%
12
Survey Participation
Targeted neighborhoods were near key air
quality monitoring sites in the SoCAB.
13
Survey Participation – Households
14
Survey Results – Household Activities
Mon-Thurs Friday Saturday Sunday
Some activities increased
from WDs to WEs by 25% to 30%
165%, including uses of 25%
– barbecues*
Estimated DOW Allocation Factor .
– recreational boats* 20%
– recreational off-road RVs*
– paints or solvents* 15%
Some activities varied little 10%
by DOW, including uses of
5%
– personal care products
– water heating 0%
BBQ Rec. Rec. Paint/
Boats Off-Rd Solvent
*see plot RVs
15
Survey Results – Household Activities
Some activities occurred at certain times of day.
Personal Care Products
– Evening: WD BBQ use*
100%
– Afternoon: Recreational boats 80%
– Morning: personal care products* 60%
40%
Some activities varied day-to-day. 20%
Diurnal Distributions
– WD BBQ use*: 8% to 12% of total in afternoon; 0%
(N=845)
(N=412)
(N=446)
(N=404)
90% in evening
Mo-Th
Sun
Sat
Fri
– WE BBQ use*: 24% to 33% of total in afternoon;
66% to 74% in evening Barbecues
100%
Some activities did not vary day-to-day. 80%
– personal care products* 60%
40%
– water heating
20%
0%
(N=102)
(N=100)
(N=60)
(N=72)
*see plot
Mo-Th
Sun
Sat
Fri
16
Survey Results – Household Activities
DOW Allocation Factor
25% Weekdays Saturday Sunday
20%
15%
10%
5%
0%
s
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WD-to-Sat WD-to-Sun
Business Type
% Reduced % Reduced
All businesses
74% 82%
(aggregate)
Gas ovens 61% 80%
Construction 90% 99%
17
Survey Results – Household Activities
Aggregate average patterns
– On WDs, business activities peaked from 8 a.m.-4 p.m.
– On WEs, business activities were evenly distributed 8 a.m.-12 a.m.
100% 100%
Business type-specific
Diurnal Distribution
80% 80% 8pm-
patterns 60%
midnight
60%
4pm- 8pm
– Activity with gas 40% 40%
ovens is sustained 20%
20% noon- 4pm
late into the evening 0%
0%
All Businesses
8am- noon
and late-night hours Gas Ovens
100% 100%
– Activities of 4am- 8am
Diurnal Distribution
80% 80%
lawn/garden and
midnight-
60% 60%
construction 4am
40% 40%
businesses peak
20% 20%
early, then drop off
0%
fast after 4 p.m. 0%
Weekday Saturday Sunday
Weekday Saturday Sunday
Lawn and Garden All Construction Companies
18
Surveys – Findings
• Some recreational activities increased 25-165% on WDs
when compared to WEs.
– Residential use of barbecues
– Recreational boats and off-road vehicles (note small sample sizes)
– Use of paints or solvents
• Diurnal patterns for some residential activities varied by
day of week.
– WD use of barbecues occurs primarily in the evening, but afternoon
use becomes significant on WEs.
• Other types of residential activities varied less than 25% by
day of week.
– Residential uses of personal care products
– Water heating for showers, baths, and automatic home appliances.
19
Surveys – Findings
• Business activities declined by 60-99% on
WEs.
• Business activity levels typically peaked
from 8 a.m. to 4 p.m. on WDs and leveled
out on WEs. However, exceptions existed.
– Work at lawn/garden and construction
businesses peaked from 4 a.m. to 4 p.m. on
WDs and was negligible on Sundays.
– Work at businesses with gas ovens peaked
later in the day on WDs and sustained through
the evening and on WEs.
20
Instrumented Vehicle Study
21
Instrumented Vehicle Study Participation
• A subset of household survey participants was
recruited.
– 68 households
– 107 vehicles
• Global positioning system (GPS) receivers with
data loggers—GeoLoggers—were installed in all
household vehicles.
• Time-activity data were recorded at 5-second
intervals for 10 to 15 days.
– Vehicle position
– Vehicle speed
• Approximately 1200 vehicle-days of data were
collected.
22
GeoLogger
23
GeoLogger Study Participation
24
GeoLogger Study – Example Data
25
GeoLogger Study – Results
Average Daily VMT per Vehicle
35
30
25
Average VMT.
20
15 29 28 29 28
26 27
25 22
10 20
5
0
Avg Mon-Fri
Monday
Avg Sat-
Sunday
Friday
Saturday
Tuesday
Thursday
Wednesday
Sun
26
GeoLogger Study – Results
Average Daily VMT per Vehicle by Road Type
Major Hwys Arterials Other Roads
20
18
18
16 16 16 16 16
16 15
14
14 13
Average VMT
12
10 8 9
8 8 8
8 7
6 5
6 5
3 4 4 4 4 4
4 3 3
2
2
0
Thursday
Avg Sat-Sun
Tuesday
Sunday
Saturday
Monday
Wednesday
Avg Mon-Fri
Friday
27
GeoLogger Study – Results
Driving patterns for high-mileage vehicles (“top 25”)
differed somewhat from those of other vehicles.
Average VMT (All Other Vehicles).
Average VMT (Top 25 Vehicles).
70
60 64 20
58 61 59
50 57 18 18
18 18 55 18 18
16 46
40 45 46 15
30 12 10
20
10
0 0
Thursday
Tuesday
Sunday
Saturday
Monday
Wednesday
Avg Mon-
Avg Sat-
Friday
Sun
Fri
Top 25 Vehicles (Left Axis) All Others (Right Axis)
28
GeoLogger Study – Results
WD-WE VMT VMT by Speed
Average Daily by Speed DistributionBin
Weekday Weekend
0.18
0.16
Fraction of Total VMT
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
5 15 25 35 45 55 65 75 >80
Speed (mph)
29
GeoLogger Study – Results
Average Hourly VMT per Vehicle
3.5
3
Mon
2.5
Tue
Average VMT
Wed
2
Thu
Fri
1.5 Mon-Fri
1 Sat
Sun
0.5
0
0 2 4 6 8 10 12 14 16 18 20 22 24
Hour of Day
(0=midnight)
30
GeoLogger Study – Results
Average Daily No. of Soaks per Vehicle
6
Average Daily No. of Soaks Observed per Vehicle .
5
4
3
5.6
4.8 4.9 5.0 5.1 5.1
2 4.1
3.8
3.6
1
0
Mon Tue Wed Thu Fri Sat Sun WD WE
Day of Week
31
GeoLogger Study – Findings
• Accruals of VMT at high speeds were observed.
Proportion of VMT
Time Period Accrued Above 65 mph
Monday-Friday 28%
Saturday-Sunday 42%
Monday-Friday, 7 a.m.-9 a.m. 28%
Monday-Friday, 4 p.m.-7 p.m. 28%
32
GeoLogger Study – Findings
• Weekly patterns of VMT were observed.
Change
Day of Average (Relative to
Percent
Week VMT Mon-Thurs) Change
Friday 29 Increase 0-4%
Saturday 25 Decrease 0-24%
Sunday 20 Decrease 22-33%
33
GeoLogger Study – Findings
• Patterns in the frequencies of trips were observed.
Day of Week Average No. of Trips
Monday-Thursday 4.8 to 5.1
Friday 5.6
Saturday 4.1
Sunday 3.5
34
Surface Street Traffic Counters
Data Logger
Pneumatic Hose
Sensors
35
Surface Street Traffic Counters
• Counters were deployed at 30 sites for 10-day periods.
36
Surface Street Traffic Counters – Example Data
Eastbound Westbound
8 per. Mov. Avg. (Eastbound) 8 per. Mov. Avg. (Westbound)
1000
=15 Min. Volume X 4
Rate (veh/hour)
800
600
400
200
0
8/2/02
8/3/02
8/4/02
8/5/02
8/6/02
8/7/02
8/8/02
8/9/02
8/10/02
8/11/02
8/12/02
Date
37
Surface Street Traffic Counters – Results
Traffic Volumes by Road Type
38
Surface Street Traffic Counters – Results
Traffic Volumes by Vehicle Type
39
Surface Street Traffic Counters – Findings
• Diurnal patterns of VMT were observed.
Day of Peak Times of
Week Pattern Peak
Monday- 7 a.m.-8 a.m.
Sharp
Friday 4 p.m.-5 p.m.
Saturday-
Gradual Noon-5 p.m.
Sunday
40
Surface Street Traffic Counters – Findings
• Patterns in traffic volumes were observed.
Change
Vehicle Day of (Relative to
Percent
Type Week Mon-Thurs) Change
Saturday Decrease 25%
Light duty
Sunday Decrease 33%
Saturday Decrease 56%
Heavy duty
Sunday Decrease 83%
41
Caltrans WIM Data
Source of Photos: Oak Ridge National Laboratory
42
Acquisition of WIM Data
43
Example WIM Data
44
WIM Data Analyses – Results
Average Diurnal Traffic Volumes: Light-Duty Vehicles
3500
3000
2500
Sun
Number of Vehicles
Mon
2000 Tues
Wed
Thurs
1500 Fri
Sat
1000
500
0
0:00
2:00
4:00
6:00
8:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
Hour
45
WIM Data Analyses – Results
Average Diurnal Traffic Volumes: Heavy-Duty Vehicles
250
200
Sun
Number of Vehicles
Mon
150
Tues
Wed
Thurs
100 Fri
Sat
50
0
0:00
2:00
4:00
6:00
8:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
Hour
46
WIM Data Analyses – Findings
Vehicle
Type Day of Diurnal Percent
Week Pattern Change
Weekday Bimodal n/a
Light duty
Decrease
Weekend Single mode
11-26%
Weekday Single mode n/a
Heavy duty
Decrease
Weekend Single mode
50-75%
47
CEMS Data
48
Acquisition of CEMS Data
• CEMS data were provided by the South
Coast Air Quality Management District.
– SoCAB major point sources
– May 2002 through October 2002
– Daily total NOx
– Confidential information withheld
49
Daily Total NOx Emissions (lbs)
100,000
120,000
140,000
20,000
40,000
60,000
80,000
0
5/1/2002
5/15/2002
5/29/2002
6/12/2002
6/26/2002
7/10/2002
7/24/2002
Date
8/7/2002
8/21/2002
9/4/2002
9/18/2002
Example CEMS Data
10/2/2002
10/16/2002
10/30/2002
50
CEMS Data Analyses – Results
Error bars represent +/- 1 standard error of the mean
60
55
NOx (1000 lbs)
50
45
40
35
30
Mon Tue Wed Thu Fri Sat Sun
Day of the Week
Original Data With June 30 Normalized
51
CEMS Data Analyses – Results
NOx Emissions (1000 lbs)
Largest 20 Other 58
Time of Week Emissions Emissions Total
Sources Sources
Average WD
40.23 9.67 49.90
(Mon-Thu)
Average Friday 37.92 9.26 47.18
Average WE
38.17 8.58 46.75
(Sat-Sun)
% Decrease
5.11% 11.25% 6.30%
WD to WE
52
CEMS Data Analyses – Findings
• NOx emissions from major point sources declined
6% on Friday-Sunday (relative to Monday-
Thursday).
• Low-emitting facilities experienced larger WD-WE
variability than high-emitting facilities.
• Emissions from high-emitting facilities declined
Friday-Sunday.
• Emissions from low-emitting facilities declined only
on Saturday and Sunday.
53
Special Studies in Neighborhoods
54
Neighborhood Special Studies
• WD-WE field observers’ diaries
• Ground-truth surveys of potential emissions sources
55
Summary and Wrap-Up
• Key Findings
• Recommendations for Modeling
• Recommendations for Further Research
• Closing Remarks
• Acknowledgments
56
Key Findings
• Activity levels for on-road mobile and business-
related sources decline on WEs relative to WDs.
• Activity levels for recreation-related sources
increase on WEs relative to WDs.
• NOx emissions from major point sources decline
on WEs.
• Substantial accrual of VMT occurs at vehicle
speeds above 65 miles per hour, especially on
WEs.
• Travel predominantly occurs on major highways,
especially on WEs.
57
Recommendations for Modeling
Average Value,
Variable Monday- Units
Thursday
Light-duty Miles per
28
VMT vehicle-day
Light-duty Soaks per
5
soaks or trips vehicle-day
58
Recommendations for Modeling
Day of Percent
Variable Change
Week Change
Friday Increase 3.5%
Light-duty Saturday Decrease 10-20%
VMT
Sunday Decrease 30%
Friday Increase 10%
Light-duty
soaks or Saturday Decrease 20%
trips Sunday Decrease 30%
59
Recommendations for Modeling
Day of Percent
Variable Change
Week Change
Heavy-duty Saturday Decrease 55-70%
VMT Sunday Decrease 75-80%
Activity levels Saturday or Increase 25-165%,
for Sunday depending on
recreational the source
sources category
Activity levels Saturday or Decrease 60-99%,
for Sunday depending on
commercial the source
sources category
60
Recommendations for Modeling
• Apply changes to activity patterns for light-duty
vehicles.
– Apply a single-mode diurnal profile to represent WE
activity patterns.
– Slightly increase the proportion of VMT occurring on
Friday afternoons and evenings.
– Adjust speed distributions to reflect high proportions of
VMT occurring at high speeds.
• Apply diurnal profiles to recreational emissions
sources favoring activities in the afternoons.
• Apply day-specific emissions data for NOx from
point sources.
61
Recommendations for Further Research
• Continue to mine the databases generated
through this project.
• Develop emission factors for on-road vehicles that
correspond to high speeds above 65 mph.
• Investigate further whether the modeled number of
starts and/or soaks per day should be reduced.
• Investigate further the extent to which emissions
should be spatially re-allocated on WEs.
• Investigate further the differences in activity
patterns for light-duty utility vehicles and
passenger vehicles.
62
Closing Remarks
• Significant WD-to-WE variability occurs
across all components of the emission
inventory: point, area, and mobile.
• Much of this variability can now be
quantified for the SoCAB.
63
Acknowledgments
• Leon Dolislager of the California Air Resources
Board (ARB) was the ARB technical contact and
Project Officer.
• Population Research Systems of San Francisco conducted
surveys and recruited study volunteers.
• Wiltec, Inc. of Antioch, California, deployed surface street
traffic counters.
• Caltrans provided freeway weigh-in-motion data.
• GeoStats of Atlanta, Georgia, supplied the in-vehicle
sensors (GeoLoggers) and performed initial data
processing and quality assurance.
• South Coast Air Quality Management District provided
continuous emissions monitoring systems data.
64
For More Information
For more information, please visit the ARB’s web
sites for “weekend effect” and air pollution
research.
www.arb.ca.gov/aqd/weekendeffect/weekendeffect.htm
www.arb.ca.gov/research/apr/past/atmospheric.htm
A copy of the final report may be downloaded from
the following location:
www.arb.ca.gov/research/abstracts/00-305.htm
65
