Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF-Chem CO tracer model

Pablo E. Saide, Gregory R. Carmichael, Scott N. Spak, Laura Gallardo, Axel E. Osses, Marcelo A. Mena-Carrasco, Mariusz Pagowski

Resultado de la investigación: Article

85 Citas (Scopus)

Resumen

This study presents a system to predict high pollution events that develop in connection with enhanced subsidence due to coastal lows, particularly in winter over Santiago de Chile. An accurate forecast of these episodes is of interest since the local government is entitled by law to take actions in advance to prevent public exposure to PM10 concentrations in excess of 150 μg m-3 (24 h running averages). The forecasting system is based on accurately simulating carbon monoxide (CO) as a PM10/PM2.5 surrogate, since during episodes and within the city there is a high correlation (over 0.95) among these pollutants. Thus, by accurately forecasting CO, which behaves closely to a tracer on this scale, a PM estimate can be made without involving aerosol-chemistry modeling. Nevertheless, the very stable nocturnal conditions over steep topography associated with maxima in concentrations are hard to represent in models. Here we propose a forecast system based on the WRF-Chem model with optimum settings, determined through extensive testing, that best describe both meteorological and air quality available measurements. Some of the important configurations choices involve the boundary layer (PBL) scheme, model grid resolution (both vertical and horizontal), meteorological initial and boundary conditions and spatial and temporal distribution of the emissions. A forecast for the 2008 winter is performed showing that this forecasting system is able to perform similarly to the authority decision for PM10 and better than persistence when forecasting PM10 and PM2.5 high pollution episodes. Problems regarding false alarm predictions could be related to different uncertainties in the model such as day to day emission variability, inability of the model to completely resolve the complex topography and inaccuracy in meteorological initial and boundary conditions. Finally, according to our simulations, emissions from previous days dominate episode concentrations, which highlights the need for 48 h forecasts that can be achieved by the system presented here. This is in fact the largest advantage of the proposed system.

Idioma originalEnglish
Páginas (desde-hasta)2769-2780
Número de páginas12
PublicaciónAtmospheric Environment
Volumen45
N.º16
DOI
EstadoPublished - 1 may 2011

Huella dactilar

complex terrain
carbon monoxide
tracer
pollution
boundary condition
topography
winter
temporal distribution
local government
air quality
subsidence
persistence
boundary layer
spatial distribution
aerosol
forecast
pollutant
prediction
modeling
simulation

ASJC Scopus subject areas

  • Environmental Science(all)
  • Atmospheric Science

Citar esto

Saide, P. E., Carmichael, G. R., Spak, S. N., Gallardo, L., Osses, A. E., Mena-Carrasco, M. A., & Pagowski, M. (2011). Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF-Chem CO tracer model. Atmospheric Environment, 45(16), 2769-2780. https://doi.org/10.1016/j.atmosenv.2011.02.001
Saide, Pablo E. ; Carmichael, Gregory R. ; Spak, Scott N. ; Gallardo, Laura ; Osses, Axel E. ; Mena-Carrasco, Marcelo A. ; Pagowski, Mariusz. / Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF-Chem CO tracer model. En: Atmospheric Environment. 2011 ; Vol. 45, N.º 16. pp. 2769-2780.
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title = "Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF-Chem CO tracer model",
abstract = "This study presents a system to predict high pollution events that develop in connection with enhanced subsidence due to coastal lows, particularly in winter over Santiago de Chile. An accurate forecast of these episodes is of interest since the local government is entitled by law to take actions in advance to prevent public exposure to PM10 concentrations in excess of 150 μg m-3 (24 h running averages). The forecasting system is based on accurately simulating carbon monoxide (CO) as a PM10/PM2.5 surrogate, since during episodes and within the city there is a high correlation (over 0.95) among these pollutants. Thus, by accurately forecasting CO, which behaves closely to a tracer on this scale, a PM estimate can be made without involving aerosol-chemistry modeling. Nevertheless, the very stable nocturnal conditions over steep topography associated with maxima in concentrations are hard to represent in models. Here we propose a forecast system based on the WRF-Chem model with optimum settings, determined through extensive testing, that best describe both meteorological and air quality available measurements. Some of the important configurations choices involve the boundary layer (PBL) scheme, model grid resolution (both vertical and horizontal), meteorological initial and boundary conditions and spatial and temporal distribution of the emissions. A forecast for the 2008 winter is performed showing that this forecasting system is able to perform similarly to the authority decision for PM10 and better than persistence when forecasting PM10 and PM2.5 high pollution episodes. Problems regarding false alarm predictions could be related to different uncertainties in the model such as day to day emission variability, inability of the model to completely resolve the complex topography and inaccuracy in meteorological initial and boundary conditions. Finally, according to our simulations, emissions from previous days dominate episode concentrations, which highlights the need for 48 h forecasts that can be achieved by the system presented here. This is in fact the largest advantage of the proposed system.",
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Saide, PE, Carmichael, GR, Spak, SN, Gallardo, L, Osses, AE, Mena-Carrasco, MA & Pagowski, M 2011, 'Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF-Chem CO tracer model', Atmospheric Environment, vol. 45, n.º 16, pp. 2769-2780. https://doi.org/10.1016/j.atmosenv.2011.02.001

Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF-Chem CO tracer model. / Saide, Pablo E.; Carmichael, Gregory R.; Spak, Scott N.; Gallardo, Laura; Osses, Axel E.; Mena-Carrasco, Marcelo A.; Pagowski, Mariusz.

En: Atmospheric Environment, Vol. 45, N.º 16, 01.05.2011, p. 2769-2780.

Resultado de la investigación: Article

TY - JOUR

T1 - Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF-Chem CO tracer model

AU - Saide, Pablo E.

AU - Carmichael, Gregory R.

AU - Spak, Scott N.

AU - Gallardo, Laura

AU - Osses, Axel E.

AU - Mena-Carrasco, Marcelo A.

AU - Pagowski, Mariusz

PY - 2011/5/1

Y1 - 2011/5/1

N2 - This study presents a system to predict high pollution events that develop in connection with enhanced subsidence due to coastal lows, particularly in winter over Santiago de Chile. An accurate forecast of these episodes is of interest since the local government is entitled by law to take actions in advance to prevent public exposure to PM10 concentrations in excess of 150 μg m-3 (24 h running averages). The forecasting system is based on accurately simulating carbon monoxide (CO) as a PM10/PM2.5 surrogate, since during episodes and within the city there is a high correlation (over 0.95) among these pollutants. Thus, by accurately forecasting CO, which behaves closely to a tracer on this scale, a PM estimate can be made without involving aerosol-chemistry modeling. Nevertheless, the very stable nocturnal conditions over steep topography associated with maxima in concentrations are hard to represent in models. Here we propose a forecast system based on the WRF-Chem model with optimum settings, determined through extensive testing, that best describe both meteorological and air quality available measurements. Some of the important configurations choices involve the boundary layer (PBL) scheme, model grid resolution (both vertical and horizontal), meteorological initial and boundary conditions and spatial and temporal distribution of the emissions. A forecast for the 2008 winter is performed showing that this forecasting system is able to perform similarly to the authority decision for PM10 and better than persistence when forecasting PM10 and PM2.5 high pollution episodes. Problems regarding false alarm predictions could be related to different uncertainties in the model such as day to day emission variability, inability of the model to completely resolve the complex topography and inaccuracy in meteorological initial and boundary conditions. Finally, according to our simulations, emissions from previous days dominate episode concentrations, which highlights the need for 48 h forecasts that can be achieved by the system presented here. This is in fact the largest advantage of the proposed system.

AB - This study presents a system to predict high pollution events that develop in connection with enhanced subsidence due to coastal lows, particularly in winter over Santiago de Chile. An accurate forecast of these episodes is of interest since the local government is entitled by law to take actions in advance to prevent public exposure to PM10 concentrations in excess of 150 μg m-3 (24 h running averages). The forecasting system is based on accurately simulating carbon monoxide (CO) as a PM10/PM2.5 surrogate, since during episodes and within the city there is a high correlation (over 0.95) among these pollutants. Thus, by accurately forecasting CO, which behaves closely to a tracer on this scale, a PM estimate can be made without involving aerosol-chemistry modeling. Nevertheless, the very stable nocturnal conditions over steep topography associated with maxima in concentrations are hard to represent in models. Here we propose a forecast system based on the WRF-Chem model with optimum settings, determined through extensive testing, that best describe both meteorological and air quality available measurements. Some of the important configurations choices involve the boundary layer (PBL) scheme, model grid resolution (both vertical and horizontal), meteorological initial and boundary conditions and spatial and temporal distribution of the emissions. A forecast for the 2008 winter is performed showing that this forecasting system is able to perform similarly to the authority decision for PM10 and better than persistence when forecasting PM10 and PM2.5 high pollution episodes. Problems regarding false alarm predictions could be related to different uncertainties in the model such as day to day emission variability, inability of the model to completely resolve the complex topography and inaccuracy in meteorological initial and boundary conditions. Finally, according to our simulations, emissions from previous days dominate episode concentrations, which highlights the need for 48 h forecasts that can be achieved by the system presented here. This is in fact the largest advantage of the proposed system.

KW - Data assimilation

KW - Deterministic model

KW - PM10 and pM2.5 forecast

KW - Santiago de chile

KW - WRF-Chem cO tracer

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U2 - 10.1016/j.atmosenv.2011.02.001

DO - 10.1016/j.atmosenv.2011.02.001

M3 - Article

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JO - Atmospheric Environment

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SN - 1352-2310

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