Study On Air Monitoring Optimization Site And Air Quality Assessment

The main purpose of this investigation is for the development of environmental monitoring and the requirement of city administration, to establish the optimized environmental monitoring network and the model of environmental quality assessment, to help the environmental researcher to make a correct environmental quality assessment, scientifically define the environmental standard, accurately provide environmental monitoring report and prediction, and administrate the environment by modern method.This thesis was centered on the optimization of environmental monitoring site. According to the environmental monitoring network of Binzhou city, the theoretical basis, principle and method of the optimized routine monitoring site in our city were established; the project of air monitoring optimization site was also proposed. The aim of selecting the optimized monitoring site is to obtain the most representative, complete, systematic and responsible air environmental monitoring information by the least monitoring sites and workload. At present there are many methods on the site optimization of air environmental monitoring and each has its characteristics. Fuzzy classification, as an optimized multi-goal decision-making method, has its specific characteristics. The article tries to improve the method properly, classifies the samples by using optimized separating method, adopt to test each site' s original measurements, arrange reliability , optimizedly classify, analyze obscure relations and examine the optimized results. Thus the optimized sites are finally determined. The method is easy to use, and has directly perceived model and natural classification. It avoids many subjective factors, accords with the demands of air environmental monitoring site, and the optimized site can represent the whole. This is one of thestudying contents of the article.The thesis also analyzed a lot of existing research results and first proposed a new method of assessing air quality, i. e. the reducing dimension B-P neural network assessment method. Based on traditional B-P neural network, this method reduced the sample data of multi-dimensional space to low-dimensional one by main component analysis, and then established the B-P network assessment model. The contrast analysis proved that this method of combining reducing dimension technology and B-P neural network was effective for the solution of environmental monitoring assessment problem in non-linear multi-dimensional system. The project based on the realistic problem, has very important application and promotion for the development of environmental monitoring and intensification of environmental administration. Moreover, the method enriches and developes the analysis and assessment model of air environment quality; and also extends the application of B-P neural network in analysis and assessment of air environment quality. This is the other studying contents of the article.