An Integrated, Near Real-Time, Web-Based Data Acquisition and Management System for Air Quality Prediction for Las Vegas Valley, Nevada

Clark County, Nevada has been criticized by US Environmental Protection Agency (US EPA) for its un-attainment air quality problem for particulate matters (PM 10 and PM 2.5) and ozone (O3) and carbon monoxide (CO). The Department of Air Quality Management (DAQM), Clark County, the regulatory and enforcement agency, is required by the US EPA to measure and report to the public the impact of aeroallergens as well as visibility and haze issues. From the long-term observation, air quality in the Las Vegas Valley is also influenced by those pollution from the neighboring states, currently around 30 monitoring stations through out the county have been in service for years to continuously monitor meteorological condition and provide valuable air quality information to the public in a timely fashion. Since the existing monitoring system was not designed to collect and process large amount of data set at a short time period, the agency cannot flexibly acquire higher resolution data sets as well as any non-scheduled data collection. Meanwhile, the much-needed data presentation and reporting features were not considered for the past. To ensure that Clark County will reach and maintain attainment of all federal air quality standards, the Nevada Center for Advanced Computational Methods (NCACM) at University of Nevada, Las Vegas (UNLV) is required by the DAQM to design a new system that can provide a multi-function data acquisition and management system. By characterized the deficiencies in the existing system, the NCACM redesign the current system that will provide a web-based work environment with new communication, model simulation and database management modules. More remote control capabilities are also included in the new system. The application will be more scalable, flexible and maintainable. The system is defined into four distinct tiers, data acquisition, data repository, data analysis and forecasting and data presentation tiers. After the 9–11 terrorist attacks, emergency response for any major cities around the country becomes a vital issue for homeland security. Through the timely data acquisition support, the system can return high-resolution data from monitoring stations for efficient model simulation. While continuously meteorological data feeding through the network, the NCACM’s newly configured Beowulf PC-clustering system calculates the possible transportation scenario around the valley and returns the best emergency scenario analysis.