Sensors Without Borders and Sensing Local presented our early analysis of the on-going BTM study on March 18th at Bengaluru's Airpocalypse: Air Pollution Problems & Solutions. Hosted by Co MEDIA LAB and Radio Active CR 90.4 MHz

1. Bengaluru’s Airpocalypse
Air Pollution Problems & Solutions
Supported by Karnataka State Pollution Control Board and ELCIA
In partnership with Society for Community Health Awareness, Research and Action (SOCHARA) &
Co Media Lab, a Radio Active CR 90.4 MHz & Citizen Matters initiative

2. Measurement of Air Quality
• DENSITY OF Coverage
How many sensors are required to cover the city?
• RANGE OF MEASUREMENT
How does the data quantify the actual experience of
air pollution?
• Data Measured and processed
How should data should be collected?
• Dissipation format
How can AQ data be put out in a way that diverse
stakeholders can use it?
• Data accuracy and reliability
How does pollution data relate to My street, My
neighbourhood, My Exposure, My health?
(Context of users)

3. • DENSITY OF Coverage
How many sensors are required to cover the city
• RANGE OF MEASUREMENT
How does the data quantify the actual experience of
air pollution?
• Data Measured and processed
How should data should be collected?
• Dissipation format
How can AQ data be put out in a way that diverse
stakeholders can use it?
• Data accuracy and reliability
How does pollution data relate to My street, My
neighbourhood, My Exposure, My health?
(Context of users)
15 Sensors
City Scale: 709 sq km2
Population: 10.2 Million
5 Sensors
Neighbourhood: 2.25 sq km2
Population: 25,000
Ambient Air
Gravimetric,
Beta Attenuation Monitoring
Local Air
Laser Optical Scattering
Wide range sensing Short range sensing
(200 m radius)
Juxtaposed with activity
patterns, health status and
perceptions of people on
Air quality data
PM10, PM2.5, SO2,
NO2, CO, O3
Also released as AQI
PM2.5
Monthly averages Per minute data
24 hr cycle
3 month long data collection
Measurement of Air Quality
KSPCB BTM Study

5. 4 Key goals
• Quantification of air pollution, and its impact.
• Recognising who is most vulnerable and how much?
• Testing the role of commodity sensors, as cost-effective
alternative for citizens to be involved in understanding
their local environment better.
• What is the role of spatial design of layouts, zoning, and
traffic in determining air quality of an area?
CONCEPT
• Develop people-first methodology for understanding
urban air pollution and conceive solutions that improve
air quality for everyone.
• Going ‘local’ is intended to potentially find a stronger
linkage between symptom-causality linkages.
How much does air quality
change due to differences in the
urban environment and other
meteorological circumstances?

6. DATA
• Site Context Data
- Meteorological Data
- Local sources of Air pollution
- Design of Urban Fabric
• Air Quality Data
• Field surveys
• Health assessment
PROCESS
ANALYSIS
• Learnings from the Field
• Data collation and Analysis
• LUR modelling - to predict air quality of areas outside
sensor locations
• Dispersion modelling
Proposals
• Developing measures for mitigation of air pollution.

7. Air Quality Data
Identificaton of suitable sensor locations
Analysing urban functions and hierachy of roads Analysing connectivity of the road, that is a key determinant
affecting traffic behaviour and road hierachy based on usage

8. Field Interviews
Perception
Behavior
Physiology
Quality of air, main sources of air
pollution, points of most exposure
Travel behavior - use of transit or
private vehicles, car sharing, etc;
Smoking or non smoking
Health ailments such as respiratory
conditions, skin allergies, etc.
Health costs
227 Surveys conducted
6 days | 9 Volunteers

9. FIELD SURVEY
Interviewee Types
Age Gender Profession

10. Nature of occupationents vs Recent residents
In BTM
Close to 60% of the sample
population has been in BTM
for over5 years
Living in BTM Nature of residence
FIELD SURVEY
Interviewee Types
Long term vs Short term residents
Close to 60% of the population
has been in BTM for over 5 years

11. Perception of Quality of air in BTM
What do people think?
0%!
10%!
20%!
30%!
40%!
50%!
60%!
70%!
80%!
90%!
100%!
D
rivers
(autos,taxis,buses)!
O
ffice
G
oers
&
Students!
O
thers!
O
utdoorW
orker-Vendors,H
aw
kers!
Policem
an!
R
esidents
orW
ork
from
hom
e!
UNHEALTHY 2!
UNHEALTHY FOR SENSITIVE
GROUPS!
MODERATE!
GOOD!
0%!
10%!
20%!
30%!
40%!
50%!
60%!
70%!
80%!
90%!
100%!
D
rivers
(autos,taxis,buses)!
O
ffice
G
oers
&
Students!
O
thers!
O
utdoorW
orker-Vendors,H
aw
kers!
Policem
an!
R
esidents
orW
ork
from
hom
e!
UN
UN
GR
MO
GO
%!
%!
%!
%!
%!
%!
%!
%!
%!
%!
%!
os,taxis,buses)!
O
ffice
G
oers
&
Students!
O
thers!
O
utdoorW
orker-Vendors,H
aw
kers!
Policem
an!
R
esidents
orW
ork
from
hom
e!
UNHEALTHY 2!
UNHEALTHY FOR SENSITIVE
GROUPS!
MODERATE!
GOOD!
Unhealthy
Unhealthy for sensitive groups
Moderate
Good0%
20%
40%
60%
80%
100%
D
rivers
(Autos,taxis,buses)
O
ffice
G
oers/Students
O
thers
O
utdoorW
orkers
(Vendors,H
aw
kers)
Policem
an
Residents/
W
ork
from
hom
e
FIELD SURVEY | PERCEPTION

12. Do people feel
differently in
different parts
of BTM?
Unhealthy
Unhealthy for sensitive groups
Moderate
Good
FIELD SURVEY | PERCEPTION
Perception of Quality of air in BTM
What do people think?

13. 0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Living & Working Living Working
TripShare between
BTM Residents
Walking
Cycle
Bus
Auto
2 Wheeler
Taxi
Pvt car
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Living & Working Living Working
Contributionto Air Pollution
Walking
Cycle
Bus
Auto
2 Wheeler
Taxi
Pvt car
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Living & Working Living Working
Exposureto Air Pollution
Walking
Cycle
Bus
Auto
2
Wheeler
FIELD SURVEY | Behavior
Modal share among trips by residents of BTM & its Impact
Trip Share
Between BTM Residents
Contribution
to Air Pollution
Exposure
to Air Pollution
Walking
Cycle
Bus
Auto
2 Wheeler
Taxi
Pvt Car

14. 0
5
10
15
20
25
30
>0.5 0.5-2 3.0-5.0 6.0-10.0 10.0-20 >20
BOTH
LIVE
WORK
> 0.5 km 0.6-2 km 3-5 km 6-10 km 10-20 km > 20 km
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
TripShare between
BTM Residents
Walking
Cycle
Bus
Auto
2 Wheeler
Taxi
Pvt car
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
TripShare between
BTM Residents
Walking
Cycle
Bus
Auto
2 Wheeler
Taxi
Pvt car
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
TripShare between
BTM Residents
Walking
Cycle
Bus
Auto
2 Wheeler
Taxi
Pvt car
Live
Work
Both
FIELD SURVEY | Behavior
Hours Spent in Traffic

15. Unhealthy
Healthy
Unhealthy
Healthy
FIELD SURVEY | Physiology
Health Ailments due to air pollution

16. 0
2
4
6
8
10
12
14
16
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97 100 103 106Simplifica
0
2
4
6
8
10
12
14
16
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97 100 103 106Simplifica
0
1
2
3
4
5
6
0 50 100250
Breathlessness
Irritationtoeyes/nose/throat
Sinusitis
SkinAllergies
asthma
FIELD SURVEY | Physiology
Juxtaposition of - Types of Health Ailments, Exposure, Type of Profession
Asthma
Skin Allergies
Sinusitis
Irritation to eyes / Nose / Throat
Breathlessness
Cafe / Shop Owner,
Employee or Manager
Office Goers & Students
Drivers
(Autos, taxis, buses)

17. Kuvempu Park
Air Quality | 1 of 5 Locations

18. Kuvempu Park
Air Quality | Seasonal Variability

19. Kuvempu Park
Air Quality | Variability across Week and Time of day

20. cOMPARISON BETWEEN REGULATORY AND COMMODITY SENSOR

21. DATA
• Site Context Data
- Meteorological Data
- Local sources of Air pollution
- Design of Urban Fabric
• Air Quality Data
• Field surveys
• Health assessment
ANALYSIS
• Learnings from the Field
• Data collation and Analysis
• LUR modelling - to predict air quality of areas
outside sensor locations
• Dispersion modelling
Proposals
• Developing measures for mitigation of air pollution.
NEXT STEPS

22. What can citizens do?