An independent component analysis (ICA) based method is designed for improving the effect of grid radio monitoring and providing an effective layout of the monitoring system, in which the source signals can be retrieved and sudden emergence of abnormal signal sources can be detected. To analyze the multiple factors affecting the performance of the method, a MATLAB simulation modeling is built. The feasibility and efficiency of the proposed ICA based method are also demonstrated.

Heavy metal contamination is one of the most concerned global environmental problems and the soil heavy metal contamination is especially severe in lead-zinc mining areas in China. In order to study the soil fungal community composition changes responding to different degree of heavy metal pollution, soil samples from the lead-zinc mine field of Yunnan Mengnuo were studied. 5 samples from the heavy metal pollution soil (HP) and other 4 from the low pollution (LP), based on the cluster analysis of heavy metal contents and the physical and chemical properties of the sample were analyzed. Genomic DNA of the soil samples were extracted and the Internal Transcribed Spacer (ITS) genes were sequenced by the high-through sequencing Illumina MiSeq. The fungal communities at different taxonomic levels (Phylum, Class, Order, Family, Genus and Species) were compared. In HP samples, the abundance of unclassified fungi were the highest, then followed by Aspergillus, Un--s-Clavulinaceae sp. and Un--s-fungal sp. ARIZ L453 respectively. In LP samples, the unclassify fungi were also high, but less than HP. The relative abundance of fungi from high to low was Geastrum, Aspergillus and Mortierella. The Representational Difference Analysis (RDA) showed that different heavy metals influence fungal community diversity and the concentrations of Pb was significantly correlated with fungal community.

Based on the air quality data of five indices in 2010 for 78 main cities of China, the research calculated the comprehensive score of urban air quality, selected ten out of 48 variables describing the climate, topography, urban development and environment management of these cities with multivariate linear regression analysis, and quantified their contribution to the urban air quality. Based on the comprehensive score of urban air quality, the authors used a stratified random sample of 30 from the 78 cities, as a training sample, to construct a radial basis function network (RBFN) model, which was used to simulate air quality of 173 main cities in China based on the natural and social-economic features, and environmental management of the cities. The results indicated that the average saturation vapor pressure, built-up urban area, elevation range, and the percentage of industry in GDP as four major dominants of urban air quality, accounting for the variation by 14.7%, 12.8%, 8.8% and 7.2%, respectively. This study broke the limitation of most previous air quality assessment models, which merely took air pollutants and meteorological factors as input. The result showed a high accuracy (R²=0.658, p<2.2×10^-14) of the RBFN model.

Due to the combined effects of lake and Gobi, the atmospheric boundary layer located in Gobi desert regions of the Bosten Lake basin is found to possess some special regional characteristics. Based on the data of the developing meteorological observation experiments conducted in the Bosten Lake of Xinjiang Province, the height characteristics of the atmospheric boundary layer from May 21 to August 28, 2013 are analyzed. The result shows that the most prominent feature of the Gobi area of the Bosten Lake Basin is that the boundary layer often has the deep convection during the typical sunny days in the summer. The statistics also shows that in 45 days out of 100 days, the average height of the atmospheric boundary layer is above 3000 m, and the maximum height reaches 4400 m. The causes of forming the deep convective boundary layer are explored. It is argued that the atmospheric thermodynamic properties and the lake wind shear are important factors to form the deep convective boundary layer.