89 Au geochemical anomalies are delineated by using 1/200000 regional geochemical exploration data. By researching regional geochemical characteristics and the relationship with the geological background, the author p...89 Au geochemical anomalies are delineated by using 1/200000 regional geochemical exploration data. By researching regional geochemical characteristics and the relationship with the geological background, the author points out that: the main factors causing high background of Au geochemical anomalies are Gaixian and Dashiqiao formation of Liaohe group, intrusions of Mesozoic intermediate-acid intrusive rocks. The elements combination types of typical anomalies are determined by using factorial analysis,cluster analysis and other mathematical methods with the combination of elements association in typical anomalies:the composite anomaly of Baiyun gold deposits is Au-As-Sb, Maoling gold deposit is Au-As- Bi-Mo, Wulong gold deposits is Au-As-Bi-W, Xiaotongjiapuzi gold deposit is Au-As-Bi-Mo-Sb. By using multivariate statistical analysis method,62 ore-caused anomaly are preferred in 89 Au geochemical anomalies delineated. On this basis, the 62 anomalies are divided into 4 kinds of anomaly types reference to elements combination types of typical anomalies,the classification results of ore-caused anomalies are: 4 geochemical anomalies of Baiyun type,36 geochemical anomalies of Maoling type,11 geochemical anomalies of Wulong type, 11 geochemical anomalies of Xiaotongjapuzi type. According to the results, the prospecting direction is provided for the futme of gold exploration.展开更多
The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method co...The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method combines the principal component analysis/absolute principal component scores (PCA/APCS) receptor model and geostatistics. The case study was conducted in an area of 31 km2 in the urban-rural transition zone of Wuhan, a metropolis of central China. 124 topsoil samples were collected for measuring the concentrations of eight heavy metal elements (Mn, Cu, Zn, Pb, Cd, Cr, Ni and Co). PCA results revealed that three major factors were responsible for soil heavy metal pollution, which were initially identified as "steel production", "agronomic input" and "coal consumption". The APCS technique, combined with multiple linear regression analysis, was then applied for source apportionment. Steel production appeared to be the main source for Ni, Co, Cd, Zn and Mn, agronomic input for Cu, and coal consumption for Pb and Cr. Geostatistical interpolation using ordinary kriging was finally used to map the spatial distributions of the contributions of pollution sources and further confirm the result interpretations. The introduced method appears to be an effective tool in soil pollution source apportionment and identification, and might provide valuable reference information for pollution control and environmental management.展开更多
文摘89 Au geochemical anomalies are delineated by using 1/200000 regional geochemical exploration data. By researching regional geochemical characteristics and the relationship with the geological background, the author points out that: the main factors causing high background of Au geochemical anomalies are Gaixian and Dashiqiao formation of Liaohe group, intrusions of Mesozoic intermediate-acid intrusive rocks. The elements combination types of typical anomalies are determined by using factorial analysis,cluster analysis and other mathematical methods with the combination of elements association in typical anomalies:the composite anomaly of Baiyun gold deposits is Au-As-Sb, Maoling gold deposit is Au-As- Bi-Mo, Wulong gold deposits is Au-As-Bi-W, Xiaotongjiapuzi gold deposit is Au-As-Bi-Mo-Sb. By using multivariate statistical analysis method,62 ore-caused anomaly are preferred in 89 Au geochemical anomalies delineated. On this basis, the 62 anomalies are divided into 4 kinds of anomaly types reference to elements combination types of typical anomalies,the classification results of ore-caused anomalies are: 4 geochemical anomalies of Baiyun type,36 geochemical anomalies of Maoling type,11 geochemical anomalies of Wulong type, 11 geochemical anomalies of Xiaotongjapuzi type. According to the results, the prospecting direction is provided for the futme of gold exploration.
基金Supported by the National Natural Science Foundation of China (No. 40971269)
文摘The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method combines the principal component analysis/absolute principal component scores (PCA/APCS) receptor model and geostatistics. The case study was conducted in an area of 31 km2 in the urban-rural transition zone of Wuhan, a metropolis of central China. 124 topsoil samples were collected for measuring the concentrations of eight heavy metal elements (Mn, Cu, Zn, Pb, Cd, Cr, Ni and Co). PCA results revealed that three major factors were responsible for soil heavy metal pollution, which were initially identified as "steel production", "agronomic input" and "coal consumption". The APCS technique, combined with multiple linear regression analysis, was then applied for source apportionment. Steel production appeared to be the main source for Ni, Co, Cd, Zn and Mn, agronomic input for Cu, and coal consumption for Pb and Cr. Geostatistical interpolation using ordinary kriging was finally used to map the spatial distributions of the contributions of pollution sources and further confirm the result interpretations. The introduced method appears to be an effective tool in soil pollution source apportionment and identification, and might provide valuable reference information for pollution control and environmental management.