Environmental Benefit from Increasing Active – A Case Study in Adelaide Transportation

South Australia’s Environment Protection Authority
Environmental Benefit from Increasing Active
Transportation – A Case Study in Adelaide
Dr Pushan Shah
Senior Scientific Officer, Air Modelling
Environment Protection Authority, Adelaide
11th April 2014
Concept of Airshed
Source: http://myecoproject.org/get-involved/pollution/causes-and-effects-of-air-pollution/
Ambient Air Quality NEPM
National Environment Protection Measure
Criteria Pollutants
• Carbon monoxide
• Nitrogen dioxide
• Photochemical Oxidants (as Ozone)
• Sulfur dioxide
• Lead
• Particles (PM10 & PM2.5)
Australian Policy Instruments
In Australia “criteria” Pollutants are defined by
National Environment Protection Measures
(NEPMs)
established by the National Environment Protection Council (NEPC)
National Air Quality Standards
(Air NEPM 2003)
Pollutant
Averaging period
Maximum
concentration
Goal/
Max no. exceedences
Carbon monoxide
8 hours
9.0 ppm
1 day a year
Nitrogen dioxide
1 hour
1 year
0.12 ppm
0.03 ppm
1 day a year
none
Photochemical
oxidants (as ozone)
1 hour
4 hours
0.10 ppm
0.08 ppm
1 day a year
1 day a year
Sulfur dioxide
1 hour
1 day
1 year
0.20 ppm
0.08 ppm
0.02 ppm
1 day a year
1 day a year
none
Lead
1 year
0.50 μg/m3
none
Particles as PM10
1 day
50 μg/m3
5 days a year
Particles as PM2.5
1 day
1 year
25 μg/m3
8 μg/m3
gather sufficient data to
inform standards process
Drivers for Air Quality (AQ)
• Emission sources and their strengths
– Point/Area Sources -e.g. industry stacks, landfills
– Motor vehicles (in urban area)
– Domestic heating e.g. wood heaters
– Other diffuse sources
• Geographical features of the region
– Surface roughness, presence/absence of hills and/or
aquatic body
• Meteorology
– Wind Speed and Direction
– Temperature and Relative Humidity
– Rainfall and cloud cover
Road Network in South Australia
National Highway = 2750 Km
Urban Arterial = 920 Km
Rural Arterial = 8600 Km
Data obtained from Various Government Departments
Ambient Particles
Size Matters!
10
Population exposure in Adelaide
•PM10 concentrations are associated with increases in
morbidity in Adelaide
•Increase in daily hospitalisations per 10 μg/m3 increase in
daily PM2.5
• Respiratory : 3% (Winter)
• Cardiovascular:
• 4.5% (Winter)
• 2.7% (All season)
Hansen A, et al, Particulate air pollution and cardiorespiratory hospital admissions in a temperate
Australian city: A case-crossover analysis, Science of the Total Environment (2012),
doi:10.1016/j.scitotenv.2011.09.027
Population exposure in Adelaide
•Statistical Analysis
•GIS based linkage of spirometry data with density of cars per
24 hour derived from motor vehicle database.
•Significant exposure response relationships in COPD
sufferers
Nitschke M, Li Q et al, 2012 Traffic Density: Effect on Chronic Obstructive Pulmonary Disease,
Manuscript under preparation
The Circle of Air Quality Management
Air Quality
Monitoring
Population
Exposure
Air Quality
Modelling
Emissions
Inventory or
Database
Air Quality
Monitoring in
Adelaide
AIR QUALITY MODELLING
Macro & Micro scale circulation
Wind Speed / Direction,
Temperature, Humidity,
uncontrolled
Mixing Height,
controlled
Soil type, topography,
Air Quality
terrain height and buildings
EMISSION RATE
Source(s)
g/sec; kg/hr or
tonnes/year
EMISSIONS INVENTORY
CONCENTRATION
μg/m3; ppm
Motor Vehicle Emissions Inventory
Pollutants
CO, PM, NOx, SO2, hydrocarbons etc
Activity
Number of Vehicles
Distance Travelled
Hot Emissions
Tyre wear, brake wear, road dust etc
Technology/Emission Standard
Mean Travelling Speed (km/h)
Cold Emissions
Technology/Emission standard
Mean Travelling Speed (km/h)
Ambient Temperature
Mean Trip Distance
MV Emissions Inventory Database
Current Focus - Air Science in South Australia
• Continuous monitoring of PM2.5 in mixed used region and developing
regions
• Continuous monitoring of other pollutants such as benzene and
toluene
• Development of an updated emissions inventory database
• Understanding population exposure
• Airshed capacity analysis of developing metropolitan region
What is alternative transport?
• Modes of transport, and systems of transport planning, which are
consistent with wider concerns of sustainability.
Finding from literature
• 2009 London Study: Shift from 10 to 30 minutes/day of
walking and bicycling:
 10-19% Cardiovascular Disease (3140-6820 deaths)
 12-13% Breast Cancer (200-210 deaths)
 7-8% Dementia (200-240 deaths)
 15% Diabetes
19% of traffic injuries
2012 Barcelona Study: 50% of short trips were replaced by bike,
22% by bus/tram and 28% are by metro/train inside Barcelona:
•
10 fewer deaths /year due to air pollution reduction
44 fewer deaths /year due to increased physical activity
0.02 fewer deaths /year due to road traffic fatality
*Woodcock J, Edwards P, Tonne C, Armstrong BG, Ashiru O, Banister D, et al. Public health benefits of strategies to reduce greenhouse-gas emissions:
urban land transport. The Lancet 2009;374:1930-1943
*Rojas-Rueda, D, de Nazelle, A, Teixido, OandNieuwenhuijsen, MJ 2012, 'Replacing car trips by increasing bike and public transport in the greater
Barcelona metropolitan area: A health impact assessment study', Environment International, vol. 49, Nov 15, pp. 100-109.
23
Method-Air pollution model
Environmental
Protection
Authority Motor
Vehicle Emission
Inventory
• Annual daily VKT
• Annual daily traffic
emissions (PM2.5)
Air Pollution Model • population-weighted
annual mean
Graphical User
concentration of PM2.5
Interface (TAPM)
The Air Pollution Model
Method-Scenario Construction
Scenarios and annual average daily vehicle travelled
kilometer (VKT)
Millions
Passenger vehicle
Commercial vehicle
40
35
30
25
20
15
10
5
0
T
ng
ng
PT
PT
30
A
i
i
l
l
0
010
o
o
s
c
c
2
t
t
2
d
y
y
e
lin
BUA ing t o c ing to c shifting shifting
war
e
o
s
T
a
B
hif
hif
s
s
20%
30%
%
%
5
10
Method-Scenario Construction
Scenarios and annual average daily PM2.5 emission
(tons)
Passenger vehicle
Commercial vehicle
1.20
1.00
0.80
0.60
0.40
0.20
0.00
PT
PT
AT
ling
ling
030
010
o
o
s
c
c
2
t
t
2
d
y
y
e
r
A
c
c
lin
BU
to
wa
to
ting shifting
e
f
o
i
s
g
g
T
a
h
n
n
i
i
s
B
hif
hif
s
s
0%
0%
2
3
%
%
5
0
1
*PT: Public transport AT: Alternative transport
Results-PM2.5 due to traffic by location
BAU 2030
Towards Alternative Transport Scenario
Results
Air Quality Benefits from Alternative Transport
VKT Reduction 
PM2.5 Reduction(μg/m3)
20%
30%
40%
0.2
0.3
0.4
Estimated Annual Change in Burden of Disease
Premature deaths
6
11
13
DALYs
52
98
118
DALY = disability adjusted life years
Results-summary of finding
• 2013 Adelaide Study: 10% passenger VKT would be replaced
by cycling, 30% by public transport in metropolitan area:
 Cardiovascular Disease (9 deaths)
 Respiratory (2 deaths)
 Lung cancer (2 deaths)
 Colon cancer (25 deaths)
 Breast cancer (11deaths)
 IHD (197deaths)
 Stroke (64 deaths)
 Type 2 diabetes (9 deaths)
 Falls (16 deaths)
 Depression (20 deaths)
31
Results-summary of finding
Estimated Annual Change in Burden of Disease (DALYs) from PM2.5 Exposure
and Physical Activity Compared with BAU in Adelaide, South Australia
Increased Public Transport
Increased Cycling
5% shifting 10% shifting
20% shifting 30% shifting
Towards
Alternative
Transport
40% shifting
Cardiovascular
22
22
29
55
66
Respiratory
8
8
11
21
25
Lung cancer
9
9
12
22
27
Colon cancer
154
318
0
0
318
Breast cancer
98
201
0
0
201
IHD
835
1746
0
0
1746
Stroke
258
531
0
0
531
Type 2 diabetes
320
660
0
0
660
Falls
94
210
0
0
210
Depression
303
622
0
0
622
Total
2062
4288
52
98
4406
Summary
 A travel mode shift towards alternative transport has the potential to
benefit air quality and reduce the population health impact from
particle matter in an Australian setting.
 A small shift from car travel distance to cycling would also lead to
considerable health co-benefits of increasing physical activity.
Slide Number 33
Limitations
 Only use PM2.5 as indicators of air pollution exposure
 Difference between emission and exposure
 Only projected the health co-benefits occurring in one “accounting year”
 Uncertainty of key assumptions
 Age issues
 Did not consider the road traffic fatalities because lack of baseline date
 TAPM limitations
34
Where to from here?
• Further work required to update emissions inventory
• Validation of models (remember „the circle of air quality management‟)
• Community risks and their long term management?
 role of traffic emissions and industrial emissions in Urban and mixed
used area?
 proximity to major roads as a risk factor?
 effect of other sources (eg.wood heaters) on air quality in Adelaide
and regional centres?
• Opportunities to collaborate as „Special Interest Group‟
Acknowledgments
 Co-authors : Ting Xia, Ying Zhang, Monika Nitschke, Shona Crabb
 Kelvyn Steer and Rob Mitchell, Environment Protection Authority
 Government of South Australia
 Korea Public Health Association
Method- Health impact assessment
Comparative Risk Assessment
estimate the burden of disease (DALYs) attributable to changes in
exposures between baseline and each scenario
AF: attributable fractions
R: relative risk
P: the proportion of the population exposed
Q: counterfactual distribution of exposure
Method-Physical activity of travellers
 Physical activity level: Sedentary, Insufficiently active and
Sufficiently active
 In Increased cycling scenarios, shifted VKT was divided in to
short-distance (< 5km), medium-distance (5-10km) and longdistance (10-15km).
one level up <5km
50% one level up
50% two levels up
two levels up
5-7.5km
7.5-10km
 Cycling distance was then converted into number of cyclists
per thousand people (evenly spread to each age-sex group).
Slide Number 38
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