Reducing the Health Impacts of Emissions from Public Transporta:on Fleets through Vehicle Assignment Op:miza:on Hadi Dowlatabadi & Brian Gouge
Ins%tute for Resources, Environment & Sustainability, University of Bri%sh Columbia, 2202 Main Mall, Vancouver, BC, Canada, V6T 1Z4
[email protected]
Source: hMp://kevino.net/images/kevino.net/fullsize/l-‐99-‐ubc-‐at-‐granville-‐and-‐broadway.jpg
Truisms • Public transit is the centrepiece of a sustainable future • Public transit strives to reduce GHG emissions and improve air quality. • Public transit faces significant fiscal constraints 2012-‐09-‐19
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With a magic wand We could: • Make alterna%ves prohibi%vely expensive • Increase ridership and with it revenues • Use increased revenues to purchase cleaner buses 2012-‐09-‐19
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What is new Idea?
• We can improve public health by reducing exposure to air pollu%on, even if we fail to reduce emission rates.
2012-‐09-‐19
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From a tailpipe to our longs
Mass emitted
Mass per volume air
Average concentration over time
kg emitted
µg/m3
µg/m3
When & Where Emissions Are
When & Where People Are
Total mass inhaled
g inhaled
Total mass deposited in body
Health outcomes based on dose
g deposited
Quality adjusted life years lost
What People Are Doing
Mass of primary PM2.5 emissions inhaled per day by the popula%on within 5000 m of the 2012-‐09-‐19 bus routes (g·∙day-‐1)
[Marshall & Nazaroff (2006) afer Smith (1993)]
5
Bus Fleet Route Characteris:cs
Model Overview Emissions Model
Dispersion Model
Popula:on Model
Bus Dispatch (Assignment) Schedule (Frequency)
X
Total Emissions
Intake Frac:on X
# Buses 2012-‐09-‐19
Non-‐Revenue Service
Intake of PM2.5 (g⋅day-‐1)
Objec:ve Func:on 6
Bus Fleet Route Characteris:cs
Emissions Model Emissions Model
Bus Dispatch (Assignment) Schedule (Frequency)
X
Total Emissions
2012-‐09-‐19
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Popula%on Density Dispersion Model
Popula:on Model
Intake Frac:on
Dispersion Model Dispersion Model
Popula:on Model
Cross Sec:on
Intake Frac:on
Dispersion Model – ½ Cross Sec%on Dispersion Model
Popula:on Model
2
Concentration (µg⋅m-3)
10
0
10
Intake Frac:on
-2
10
0
2012-‐09-‐19
1000
2000 3000 4000 Distance from bus route (m)
5000 10
Exposure Model – ½ Cross Sec%on Dispersion Model 2
8
10 Zon e 1 Zon e 2 Zon e 3 Zon e 4 Zon e 5 Zon e 6 Zon e 7
0
10
6
10 Intake Frac:on
-2
0
2012-‐09-‐19
4
10
Population
Concentration (µg⋅m-3)
10
10
Popula:on Model
2
1000
2000 3000 4000 Distance from bus route (m)
10 5000
11
Route Intake Frac%ons Primary PM2.5 Intake Fraction (10-6)
35
30
BTC Depot Routes
Electric Routes
Diesel Routes
Dispersion Model
Popula:on Model
25
20
15
10
Intake Frac:on
5
0
2012-‐09-‐19
Metro Vancouver Routes Ordered by Intake Fraction
12
Intake Frac%on vs. Intake 30
Diesel iF
Diesel BRT iF
Diesel Intake
Diesel BRT Intake
40
25
20
50
30
2
32
20
44
99
15
84
15
27
22
29
26
43
10
0
2012-‐09-‐19
41
10
5
Translink Vancouver City Diesel Routes (ordered by iF)
Primary PM2.5 Intake (mg/day)
Primary PM2.5 Intake Fraction (10-6)
50
0
13
Bus Fleet Route Characteris:cs
Op%miza%on Emissions Model
Dispersion Model
Popula:on Model
Bus Dispatch (Assignment) Schedule (Frequency)
X
Total Emissions
Intake Frac:on X
# Buses 2012-‐09-‐19
Non-‐Revenue Service
Intake of PM2.5 (g⋅day-‐1)
Objec:ve Func:on 14
Op%miza%on Results 175%
Fuel
Total PM2.5
160% 147%
Intake of PM2.5
150% 125% 100% 66%
75%
73%
50% 25% 0%
0% 0% 0% Minimize Intake Best Case Scenario
2012-‐09-‐19
7% Random
10% Maximize Intake Worst Case Scenario 15
Summary IF a transit authority has a fleet of buses with diverse emission characteris%cs, we can use bus assignment op%miza%on to reduce health impacts of transit opera%ons significantly (at a frac%on of the cost of buying new buses).
2012-‐09-‐19
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In addi%on We can use extensions to this work to: – Allocate buses more efficiently to different garages serving a region. – Decide between alterna%ve bus technologies for new investments.
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Acknowledgements
• Research partners
• Funders
C DMC Climate Decision-‐making Center Carnegie Mellon University
Ques:ons?
Source: hMp://picasaweb.google.com/chris.dus%n/808#5236704901832350242
[email protected]
99 B-‐Line Case Study
2012-‐09-‐19
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A typical route transect
Change in eleva%on
Bus stops Traffic lights
Change in popula%on density
2012-‐09-‐19
Minor cross-‐roads Pedestrian Popula%on 21
Transit & Popula%on Trends Other Trolley Bus Light Rail Heavy Rail Paratransit Commuter Rail Bus Population
20
15
350 300 250 200 150
10
100
Population (Millions)
Passenger Trips (Billions)
25
5 50 0 1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
0 2010
Sources: Gouge (2012, PhD thesis) based on (APTA,2006, 2011, United States Census Bureau,2000, 2012) 2012-‐09-‐19
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Bus Fleet Diversity 0%
1% 8% Diesel Hybrid
18%
CNG Electricity 7%
66%
Gasoline Other
2012-‐09-‐19
Source: Transit bus distribu:on by energy source (APTA,2011).
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Buses Technologies & Cost Bus Category
Average Cost (2010 USD)
Standard1 Diesel
377,000
Standard1 CNG
456,000
Standard1 Diesel Hybrid
562,000
Articulated2 Diesel
659,000
Articulated2 Diesel Hybrid
804,000
2012-‐09-‐19
Source: Transit bus distribu:on by energy source (APTA,2011).
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Bus Fleet Characteris%cs Bus Type
Costs $/km
PM2.5 g/km
Nox
g/km
GWC100
gCO2e/km
Old Fleet
New Fleet
40DO
0.889
0.662
17
2516
95
0
40 ft Old (2Stroke) Diesel OxCatb
40DB2
0.656
0.212
22
1732
294
0
40 ft Baseline Diesel with OxCat
40DB
0.594
0.109
12.3
1546
54
170
40 ft Baseline Diesel with OxCat
40DA
0.625
0.0244
6.83
1590
193
170
40 ft Advanced Diesel with DPFc
40DH
0.587
0.0125
5.2
1190
1
170
40 ft Hybrid Diesel with DPF
60DB
1.042
0.196
16.3
2984
76
37
60 ft Baseline Diesel with OxCat
60DA
1.017
0.0628
12.2
2850
10
37
60 ft Advanced Diesel with DPF
60DH
0.821
0.0125
8.97
1860
26
37
60 ft Hybrid Diesel with DPF
40CG
0.600
0.0168
12.4
1635
43
170
40 ft CNG with OxCat
2012-‐09-‐19
Source: Brian Gouge (PhD Thesis 2012)
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Fleet
OLD NEW
Objective (Minimise)
Cost
Fuel
GWCc
NOX
PM2.5
PM2.5 Intake (Exposure)
Costb
Best
1.01
0.06
5.64
3.04
14.1
Fuel
0.33
Best
0.16
6.90
7.86
18.7
GWCc
0.08
0.51
Best
4.69
3.17
14.2
NOX
3.02
4.06
3.62
Best
29.7
41.9
PM2.5
0.14
1.59
0.21
4.47
Best
12.5
PM2.5 Intaked Worst (Maximise)
1.08
2.30
1.50
9.63
12.9
Best
8.79
11.7
12
35
108
123
Costb
Best
2.15
0.25
9.89
41.3
47.1
Fuel
0.34
Best
0.00
4.29
43.2
48.9
GWCc
0.34
0.00
Best
4.29
43.2
48.9
NOX
0.66
0.41
0.19
Best
25.7
34.1
PM2.5
0.47
4.77
0.88
4.47
Best
10.3
PMI2.5 Intaked Worst (Maximise)
0.93
5.82
2.31
6.06
9.99
Best
2.88
15.3
9.93
28.1
96.2
107
2012-‐09-‐19
Source: Brian Gouge (PhD Thesis 2012)
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