Salvador Enrique Puliafito

New Approaches for Urban and Regional Air Pollution Modelling and Management

Air pollution is a complex problem that plays a key role in human well-being, environment and climate change. Since cities are, by nature, concentrations of humans, materials and activities, air pollution is clearly a typical phenomenon associated with urban centres and industrialized regions (Fenger, 1999; de Leeuw et al., 2001). Since approximately half the population of the world lives in medium to large cities, it is essential to evaluate the air quality levels of the atmosphere in order to assess the possible health impact from exposition to pollutants (World Health Organization [WHO], 2002; Brunekreef & Holgate, 2002). Additionally, air pollution is not only a human health problem: the effects of pollution in ecosystems and materials are well identified and documented (Fowler et al., 2009); economic costs can also be associated with poor air quality, and with political/governmental measures taken in order to prevent or reduce pollution (Muller & Mendelsohn (2007)). The simplest technique for evaluating patterns of local-scale urban air pollution concentration involves the interpolation of ambient concentrations from existing monitoring networks (Ballesta et al., 2008; Ferretti et al., 2008). However, the measured data from these stations are not necessarily representative of areas beyond their immediate vicinity, since concentrations of pollutants in urban areas may greatly vary on spatial scales that range from tens to hundreds of metres. At the same time, the temporal behaviour of primary and secondary pollutants changes considerably between day and night due to solar radiation, so that daily average measurements become unsatisfactory in determining or explaining high pollution episodes. Air Quality Models (AQMs) are mathematical tools that simulate the physical and chemical processes that involve air pollutant dispersion and reaction in the atmosphere. Furthermore, they improve the limitations of monitoring networks by providing prediction of the temporal and spatial distribution of actual pollution levels. Modelling studies, in combination with air quality monitoring, are then essential and complementary tools for long and short term air pollution control strategies. A well calibrated model is a unique tool that allows the representation of the atmospheric dynamics and chemistry. Thus, AQMs have become a valid instrument for environmental managers in many activities, such as

High resolution satellite derived erodibility factors for WRF/Chem windblown dust simulations in Argentina

A proper representation of dust sources is critical to accurately predict atmospheric particle concentration in regional windblown dust simulations. The Weather Research and Forecasting model with Chemistry (WRF/Chem) includes a topographic-based erodibility map originally conceived for global scale modeling, which fails to identify the geographical location of dust sources in many regions of Argentina. Therefore, this study aims at developing a method to obtain a high-resolution erodibility map suitable for regional or local scale modeling using WRF/Chem. We present two independent approaches based on global methods to estimate soil erodibility using satellite retrievals, i.e. topography from the Shuttle Radar Topography Mission (SRTM) and surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). Simulation results of a severe Zonda wind episode in the arid central-west Argentina serve as bases for the analysis of these methods. Simulated dust concentration at surface level is compared with particulate matter measurements at one site in Mendoza city. In addition, we use satellite aerosol optical depth (AOD) retrievals to investigate model performance in reproducing spatial distribution of dust emissions. The erodibility map based on surface reflectance from MODIS improves the representation of small scale features, and increases the overall dust aerosol loading with respect to the standard map included by default. Simulated concentrations are in good agreement with measurements as well as satellite derived dust spatial distribution.