Presented at MIT CENSAM Workshop on June 2014 as a part of collaborative project between ETH and MIT in Singapore. Air pollution at street level: http://censam.mit.edu/research/Pages/Characterization%20of%20airborne%20particles%20in%20outdoor%20environments%20of%20Singapore.aspx related publication: http://www.atmos-meas-tech.net/8/3563/2015/ poster:http://censam.mit.edu/research/CENSAM%20Publications/Urban/Characterization%20of%20airborne%20particles%20in%20outdoor%20environments%20of%20Singapore/Vahid%20poster.pdf

1. svm@arch.ethz.ch
SEC
Finding Candidate Locations for Aerosol Pollution
Monitoring at Street Level Using a Data-Driven
Methodology
Vahid Moosavi1, Gideon Aschwanden1, Erik Velasco2
[1] {Future Cities Laboratory, ETH Zurich, 8092 Zurich, Switzerland}
[2]{Singapore-MIT Alliance for Research and Technology (SMART), Center for
Environmental Sensing and Modeling (CENSAM), Singapore}
June 2014
1

2. 2
Problem Statement
Real exposure might be different than reports
But it is hard to measure
And hard to model and simulate

3. 3
Hypothesis: There is nonlinear relations between urban parameters
and aerosol concentrations at the ground level.
Key Idea:
So, what if we are able to capture this nonlinearity empirically using data-driven
modeling methods?
More than 80
urban parameters
And 7 aerosols

4. Methods and Results
Self Organizing Maps
(SOM)
Hypothesis Testing