1.Institute of Geology and Mining Engineering, Xinjiang University, Urumqi , China；2.No.161 Geological Exploration Team,Bureau of Xinjiang Coalfield Geological, Urumqi ,China

In order to find out the enrichment of elements in Xishanyao Formation coal,Hanshuiquan mining area, Santanghu Coalfield, Xinjiang, the indication of element characterization index to the environmentis analyzed toreveal the characteristics of sedimentary environment change.Based on coalfield geology, geochemistry and other theoretical methods, with low temperature ashing, ICP-MS and other means, the content data of trace elements and rare earth elements in coal is obtained and analyzed.The results show that trace elements V, Cu, As, Rb and Sr are relatively enriched in coal. The distribution forms of rare earth elements show that the light rare earth element (LREE) is obviously deficit while the heavy rare earth element (HREE)is relatively enriched and it also indicates that Ce shows negative anomaly and Eu appears to positive anomaly. The content of rare earth elements after low temperature ash is much higher than that of untreated, which indicates that most of the rare earth elements exist in organic matter.The enrichment of V and Ga in coal seams in the study area is related to the high content of clay minerals; Cu is associated with pyrite; As mainly exists in the form of arsenopyrite. The contents of δEu, Sr/Ba, V(V+Ni), V/Cr, Ni/Co and S generally reflect that the sedimentary environment in the study area is continental fresh water reduction environment and partly weak oxidation environment. No.7, 9, 17, 22 coal seams are in Paleo-oxidizing environment, No.8, 13, 14, 15, 18, 19, 20 coal seams are in a reducing environment and Paleo-environment is characterized by alternating redox reduction in vertical direction. It is inferred that the coal-bearing rock series is a lake transgression process in the main body of sedimentary stage of Xishanyao Formation in Santanghu Coalfield, accompanied by many small-scale lake transgression-lake regression processes.

国家自然科学基金资助项目（41662010）；新疆维吾尔自治区青年教师科研培育基金资助项目（XJEDU2016S038）