HR: 09:32h
AN: A21G-07    [Abstracts]
TI: Photochemical Modeling at Santiago, Chile (33.5° S, 70.6° W)
AU: * Jorquera, H
EM: jorquera@ing.puc.cl
AF: Pontificia Universidad Catolica de Chile, Avda. Vicuna Mackenna 4860 Macul, Santiago, 6904411, Chile
AU: Castro, J
EM: jcastrom@uc.cl
AF: Pontificia Universidad Catolica de Chile, Avda. Vicuna Mackenna 4860 Macul, Santiago, 6904411, Chile
AB: The greater metropolitan region of Santiago, Chile (6.5 million inhabitants) is located in a basin with complex topography that promotes pollutant trapping below the subsidence-based thermal inversion. The (diurnal) upwind land use consists of agriculture activities that contribute to the emissions of the city itself. Santiago is the 7th Latin American city in population, and 40% of the country's inhabitants live there. Steady economic growth in the last 20 years has resulted in a fast increment of car ownership, industrial activity, fuel consumption, etc. As a result of air quality regulations, ambient PM10 and PM2.5 concentrations have been reduced significantly between 1990 and 2000. However, ozone ambient concentrations do not show a downward trend, and the 98th percentile of the 8-h moving average consistently exceeds the 120 (μg/m3) standard. Also, the current annual ambient PM2.5 concentration is near 30 (μg/m3), twice the US standard. We have developed an emissions inventory for the greater metropolitan region of Santiago (base year 2005), including agriculture and biogenic emissions at the regional scale. We use the MM5 mesoscale modeling system coupled with the CAMx air quality model to: a) assess the quality of the emission inventory database, b) improve emission estimates by means of inverse modeling, c) model ozone formation and transport, with an emphasis on estimating ozone sensitivities with respect to different geographical regions and emission sources. We do this analysis for two multi-day episodes in spring and summer seasons. Results of constraining CO, VOC, NOx and primary PM emissions with ambient monitoring data using a Kalman filter approach will be shown, along with the results for the ozone sensitivity estimates.
DE: 0345 Pollution: urban and regional (0305, 0478, 4251)
DE: 3307 Boundary layer processes
DE: 3329 Mesoscale meteorology
DE: 3333 Model calibration (1846)
DE: 3355 Regional modeling
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting