Design Of Real-time Evaluation Display System For Atmospheric Heavy Metal Pollution

In recent years, fog and haze is high frequency in many of China’s provinces, and caused health hazards aroused widespread concern, but as a major factor affecting air quality, heavy metal pollution neither carry out any monitoring program of heavy metal pollutants nor establish heavy metal of air quality control release system. In this situation of environmental pollution and application requirements, a system to evaluation real-time atmospheric heavy metal under Visual Studio 2008 and MFC development environment.The system uses C/S architecture, database taken advantage of SQL Server 2005 to store and manage system information. For heavy metal monitoring information, combined signed factor pollution index with potential ecological risk index method to environmental pollution assessment and classification which was to lay groundwork for system data collection, statistics and display.Firstly, using ADO to access and realize the system interacts with the database information; Secondly, realizing the integration of heavy metals monitoring data and geographic information, achieving real-time updates KML node, showing heavy metal pollution data and levels by balloon, assessing the overall pollution status by contours and pollution distribution map of inquiring province based on Google Earth and baidu map; Thirdly, adopting graphs, histograms showing the variation of real time,24h and week pollution data, determining the location of sources, real-time broadcast, contamination exceeds a critical value may cause alert, released heavy metal monitoring results comprehensively and visually. Finally, the environmental and functional testing is realized to guarantee the system’s safe and reliable operation.Real-time heavy metal monitoring data always have missing and wrong. For this problem, the RBF neural network spatial interpolation method is established based on the existing spatial interpolation and achieved good results, the model not only has higher accuracy and is suitable for forecasting atmospheric air pollutants. An effective processing method is provided to environmental services staff and to lay the foundation for the establishment of the continuous heavy metal data set.