Air pollution is associated with significant health effects on urban populations. American Lung Association has reported that nearly half the people in the United States live in counties where they are exposed to unhealthful levels of air pollution. Two air pollutants of great concern are ozone and PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 ìm) due to their adverse human health effects. Health effects of ozone include increased rates of hospital admissions, exacerbation of respiratory illnesses and others. PM2.5 has been studied to increase risks of heart attacks, lung function indices and other health effects. Timely and effective air pollution alerts can provide people with information they need to protect their health from air pollution. Regional air pollution is predicted by using numerical air quality forecasting models which are one of the core elements of contemporary Urban Air Quality Management and Information Systems. Air quality forecasting has become a common practice in recent years for local and state air quality management agencies to inform the public air pollution that may pose a risk to human health and received increasing attentions. Today, about 300 cities nationwide are issuing air pollution alerts based on predicted concentrations of known pollutants such as ozone and particle pollution. The air pollution alerts are currently delivered to the public in three ways: (1) internet posting; (2) emails/text messages; and (3) broadcasting through media. One major issue for these methods is the effectiveness of the information delivery because people in forecasted pollution areas may not have an access to internet or media. Alerts through text messages require users to subscribe air pollution alerts and customize their location information. However, people who receive the alerts through text messages may not be in the area where air pollution is forecasted because predetermined location information may not be correct. A smart phone is a mobile phone equipped with advanced computing capabilities and applications. In recent years, demands and popularities of smart phones are increasing tremendously and numerous location-related applications are being developed. Smart phones with location-aware capabilities have a wide range of applications, such as context-based advertising, traffic planning, route predictions, early warning systems, etc. This study takes advantage of the location-aware capabilities of smart phones to improve the effectiveness of the current air pollution alert systems. Smart phone apps are developed to deliver timely and effective alerts to smart phone users in the areas where air pollution is forecasted. The effectiveness of the new air pollution alert system is accessed, and the results will be presented. These apps can be customized and applied to other types of disaster alerts, such as flooding, hurricanes, etc., through forecasting tools and mobile devices with location-aware capabilities.