Universidade de São Paulo 
Instituto de Astronomia, Geofísica e Ciências Atmosféricas 
Air pollution modeling in the Estad...
1 Background 
 Expanded Area: Sao Paulo, 
Campinas, Santos and more
1 Background 
E=FE∗VF∗TV∗L 
Activity Level
Top-Down 
Where are the 
cars?
But in reality...
Bottom-up 
Dynamics of 
vehicular flux 
should be 
incorporated to 
emissions models
1 Background 
E=FE∗VF∗TV∗L 
Activity Level
Road 
Network 
Activity 
Vehicular 
flow 
Vehicular 
Technology 
Standards 
Municipality 
Street 
Models 
Traffic Counts 
...
Metodos 
206 points for 
counting 
Regressions: 
●Distribution Poisson 
●Zero Inflated 
Negative Binomial 
●Normal
Model 
βo: intercept; β1: estimate; TR: Type of Street; ε: Error 
0 5 10 15 20 25 30 
2.5 
2 
1.5 
1 
0.5 
0 
Distribuição...
RMSP RMC RML RMS RMSP RMC RML RMS Santiago AMBA 
IAG CETESB DICTUC D'Angiola 
1400000 
1200000 
1000000 
800000 
600000 
4...
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Emissions Inventories for SP (Brasseur) ODP

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Emissions Inventories for SP (Brasseur) ODP

  1. 1. Universidade de São Paulo Instituto de Astronomia, Geofísica e Ciências Atmosféricas Air pollution modeling in the Estado de São Paulo using a bottom-up emissions inventory Orientadora: Rita Yuri Ynoue Aluno: Sergio Ibarra Espinosa 2/10/14
  2. 2. 1 Background  Expanded Area: Sao Paulo, Campinas, Santos and more
  3. 3. 1 Background E=FE∗VF∗TV∗L Activity Level
  4. 4. Top-Down Where are the cars?
  5. 5. But in reality...
  6. 6. Bottom-up Dynamics of vehicular flux should be incorporated to emissions models
  7. 7. 1 Background E=FE∗VF∗TV∗L Activity Level
  8. 8. Road Network Activity Vehicular flow Vehicular Technology Standards Municipality Street Models Traffic Counts Regression and Traffic Simulations Statistical Evaluation IAG HBEFA Emissions Estimation Vehicular flow Copert 4 CETESB WRF Chem 24 hours profile Meteorology Emissions Street-hour
  9. 9. Metodos 206 points for counting Regressions: ●Distribution Poisson ●Zero Inflated Negative Binomial ●Normal
  10. 10. Model βo: intercept; β1: estimate; TR: Type of Street; ε: Error 0 5 10 15 20 25 30 2.5 2 1.5 1 0.5 0 Distribuição normalizada 800:900 segunda São Paulo RM São Paulo seg ter qua qui sex sab dom 0 5 10 15 20 25 30 3 2.5 2 1.5 1 0.5 0 Distribuição normalizada 800:900 segunda São Paulo RM Campinas seg ter qua qui sex sab do m
  11. 11. RMSP RMC RML RMS RMSP RMC RML RMS Santiago AMBA IAG CETESB DICTUC D'Angiola 1400000 1200000 1000000 800000 600000 400000 200000 0 Emissions inventories (t/y) CO (t/a) Nox (t/a) COV (t/a)

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