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Outlook M-cities in South America Building inventories Inverse modeling Summary Credit: C. Mayhew & R. Simmon (NASA/GSFC), NOAA/ NGDC, DMSP Digital ArchiveR.

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Presentation on theme: "Outlook M-cities in South America Building inventories Inverse modeling Summary Credit: C. Mayhew & R. Simmon (NASA/GSFC), NOAA/ NGDC, DMSP Digital ArchiveR."— Presentation transcript:

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2 Outlook M-cities in South America Building inventories Inverse modeling Summary Credit: C. Mayhew & R. Simmon (NASA/GSFC), NOAA/ NGDC, DMSP Digital ArchiveR. SimmonNASAGSFCNOAANGDC DMSP

3 South American Megacities > 75% of South Americans live in M-cities!!

4 In most cities, environmental policies are targeted at first towards diminishing acute health impacts Sao Paulo, Brazil Santiago, Chile

5 When the objectives become more ambitious (long-term impacts, more expensive and less obvious measures, etc.) Emissions have to be more accurate and be used in combination with models Regional monitoring networks are needed Traffic emissions and planning become foci

6 2+2=4, right? SA M-cities concentrate population, environmental problems and resources M-cities are global change drivers This issue can merge efforts and strenghten the region

7 UMESAM-Objectives To establish an international network of scientists able to connect local air quality initiatives and global environmental change research in South America. To provide a common and comparable methodology that combines bottom-up and top-down inventory building techniques and that can be readily applied in South American cities for estimating, as a first and triggering step, emission inventories for mobile sources. To reduce the uncertainties in emissions inventories of several major pollutants, including CO, NOx, particulate matter and GHGs, at both continental and urban scales, instrumental to air quality and climate modeling.

8 Atmospheric science Appl. Mathematics Computer Science Mechanical & Chemical Engineering +6 students Started March 29 2004

9 UMESAM ACTIVITIES Measurent of vehicular activity and CO emission estimates in Lima, Sao Paulo, Santiago, Bogotá Direct and inverse simulations at various scales using CO observations as constrain Collaboration Network Methodology New inventories for mobile sources Inventory Optimization Training

10 Building inventories for mobile sources Good statistics, traffic modeling and local emission factors, i.e., EXPENSIVE vehicle type driving behavior local conditions

11 E.g., Santiago’s and Sao Paulo’s already have Inventories!

12 International Vehicle Emission Model (IVE) 1.Choose representative streets 2.Determine fractions of vehicle technology classes (video taping, parking lots survey) 3.Identify main driving patterns (GPS) 4.Determine start patterns

13 IVE: Unexpensive, Fast, Comparable +Bogotá

14 Inventories for Buenos Aires & Bogotá…ongoing! Bogotá

15 Regional Global Modeling at various scales Local Pétron et al, Longo et al, Muñoz et al

16 E i, i=1,...n M S j, j=1,...m MtMt $… Modeling

17 J1) Best Linear Unbiased Estimator It will be used to better estimate source strength and time variation for Santiago’s and Sao Paulo’s CO inventories

18 J2) Adjoint Improve inventories….optimal monitoring network design

19  … UMESAM is a pilot network project functional for better understanding (science) and management both at local (city-by-city) and regional/continental scales Common methodologies for building and evaluating emission inventories Optimization of available inventories for Santiago and Sao Paulo New inventories for Buenos Aires, Bogotá & Lima A NETWORK IS AT WORK!!

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