Numerical air quality forecast modeling system: Mexico case study

Abstract

Air pollution has effects on ecosystems, infrastructure and human health, and therefore it is important to develop pollution exposure reduction. Large cities, like Mexico Megacity, have high pollution concentration episodes, even though an air quality monitoring network can measure and issue alarms when high level of air pollutants concentrations are reached, the population is exposed to harmful air pollutants before being aware of it. Air quality forecast information can reduce exposure to air pollution high concentrations for sensitive and general public. This work describes an operative air quality forecast modeling (AQFM) system. The modeling domain covers Mexico country, it uses a meteorology-chemistry coupled model in a high performance computing hardware, the AQFM forecasts primary (carbon monoxide CO, sulfur dioxide SO2) and secondary (ozone O3) air pollutants, and the time span is for up to 42 h starting at 12Z. Model results are given in terms of pollutant concentration distribution images, which are displayed in a web site. System like this can be applied for regional or urban areas in order to advice and to reduce pollution exposure.