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Water quality characterization of road runoff in urban area of Guangzhou, China
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作者 Huayang GAN Muning ZHUO +1 位作者 Dingqiang LI yongzhang zhou 《Chinese Journal Of Geochemistry》 EI CAS 2006年第B08期144-144,共1页
关键词 广州市 城市道路 水质 降水量 水体污染
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Mantle sources of Cenozoic volcanoes around the South China Sea revealed by geochemical and isotopic data using the principal component analysis
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作者 Shuangshuang CHEN Zewei WANG +1 位作者 Rui GAO yongzhang zhou 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2023年第2期562-574,共13页
Principal component analysis(PCA)was employed to determine the implications of geochemical and isotopic data from Cenozoic volcanic activities in the Southeast Asian region,including China(South China Sea(SCS),Hainan ... Principal component analysis(PCA)was employed to determine the implications of geochemical and isotopic data from Cenozoic volcanic activities in the Southeast Asian region,including China(South China Sea(SCS),Hainan Island,Fujian-Zhejiang coast,Taiwan Island),and parts of Vietnam and Thailand.We analyzed 15 trace element indicators and 5 isotopic indicators for 623 volcanic rock samples collected from the study region.Two principal components(PCs)were extracted by PCA based on the trace elements and Sr-Nd-Pb isotopic ratios,which probably indicate an enriched oceanic island basalt-type mantle plume and a depleted mid-ocean ridge basalt-type spreading ridge.The results show that the influence of the Hainan mantle plume on younger volcanic activities(<13 Ma)is stronger than that on older ones(>13 Ma)at the same location in the Southeast Asian region.PCA was employed to verify the mantle-plume-ridge interaction model of volcanic activities beneath the expansion center of SCS and refute the hypothesis that the tension of SCS is triggered by the Hainan plume.This study reveals the efficiency and applicability of PCA in discussing mantle sources of volcanic activities;thus,PCA is a suitable research method for analyzing geochemical data. 展开更多
关键词 volcanic rocks geochemical indicators mantle source principal component analysis South China Sea
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Environmental response to ore deposits and mining of the Diaojiang River basin, Guangxi (South China)
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作者 yongzhang zhou Zhi DANG +5 位作者 Xianzhi PENG Zhijun YANG Chengbo ZHANG Xiaoqiang YANG Shanming FU Yuyan ZHAO 《Chinese Journal Of Geochemistry》 EI CAS 2006年第B08期40-41,共2页
关键词 土壤环境反应 重金属 环境污染 环境地质化学 矿山污染
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Soil pollution by polycyclic aromatic hydrocarbons: A comparison of two Chinese cities 被引量:8
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作者 Jin Ma yongzhang zhou 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2011年第9期1518-1523,共6页
Soil samples from Huizhou and Zhanjiang,China were analyzed for 16 priority polycyclic aromatic hydrocarbons (PAHs) with harmonized sampling,sample extraction and analysis quantification methods.The concentrations a... Soil samples from Huizhou and Zhanjiang,China were analyzed for 16 priority polycyclic aromatic hydrocarbons (PAHs) with harmonized sampling,sample extraction and analysis quantification methods.The concentrations and sources of PAHs in soil samples of the two cities were compared.Almost all of the PAH components were detectable in 103 soil samples.The concentrations of ∑ PAHs ranged from 35.40 to 534.5 μg/kg in soil samples from Huizhou,and ranged from 9.50 to 6618.00 μg/kg in samples from Zhanjiang.Evident differences of concentrations,compositions and sources of PAHs in soils were observed between the two cities.The average concentrations of individual component and the sum of a group of PAHs in soil samples from Zhanjiang were significantly higher than those in Huizhou (P 0.05).Phe,Flu,Pyr,Bbf and Baa were the dominant PAH components both in soil samples from Huizhou and Zhanjiang.Except for these five components,Bap,I1p,Daa and Bgp were also the dominant PAH components in soil samples from Zhanjiang.Coal combustion and liquid fossil fuel combustion were the same sources of PAHs in the two cities with different contributions,and petroleum played a key role in PAHs release in Zhanjiang. 展开更多
关键词 polycyclic aromatic hydrocarbons (PAHs) urban soil SOURCES principal component analysis (PCA)
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