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Discriminating ore fertile and barren granites using zircon Ce and Eu anomalies – Perspective from late Mesozoic (Yanshanian) granites in South China
Journal Pre-proofs Discriminating ore fertile and barren granites using zircon Ce and Eu anomalies – Perspective from late Mesozoic (Yanshanian) granites in South China Xingyuan Li, Quanzhou Gao, Hao Song, Jingru Zhang, Chun-Kit Lai PII: DOI: Reference:
S0169-1368(18)31022-9 https://doi.org/10.1016/j.oregeorev.2019.103105 OREGEO 103105
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Ore Geology Reviews
Received Date: Revised Date: Accepted Date:
12 December 2018 18 May 2019 29 August 2019
Please cite this article as: X. Li, Q. Gao, H. Song, J. Zhang, C-K. Lai, Discriminating ore fertile and barren granites using zircon Ce and Eu anomalies – Perspective from late Mesozoic (Yanshanian) granites in South China, Ore Geology Reviews (2019), doi: https://doi.org/10.1016/j.oregeorev.2019.103105
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Discriminating ore fertile and barren granites using zircon Ce and Eu anomalies – Perspective from late Mesozoic (Yanshanian) granites in South China Xingyuan Lia, b*, Quanzhou Gaoa*, Hao Songc, Jingru Zhangd, Chun-Kit Laie, f a. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China b. Department of Geology, University of Regina, Regina, S4S 0A2, Canada c. Chengdu University of Technology, Chengdu, 610059, China d. Guangdong Province Academic of Environmental Science, Guangzhou, 510045, China e. Faculty of Science, Universiti Brunei Darussalam, Gadong, Brunei Darussalam f. ARC Centre of Excellence in Ore Deposits (CODES), University of Tasmania, Hobart, Tasmania, Australia
*
Corresponding
authors:
X.
Li
([email protected])
and
Q.
Gao
([email protected]) Abstract: Redox conditions are widely considered to be important to magma fertility, and have been estimated using different proxies, notably the biotite Fe3+/Fe2+ ratios and zircon Ce and Eu anomalies. In this research, we compiled a large number of zircon REE data from both the fertile (Cu–(Au)–Mo, Cu−Pb–Zn, W–Sn, W and Sn) and barren Yanshanian (Jurassic-Cretaceous) granites from South China to test whether zircon REE compositional differences can differentiate various deposit types and discriminate fertile intrusions from barren ones. We propose a modified method to calculate Ce anomalies (CeN/CeN*, chondrite-normalized) using all MREEs and HREEs (except Eu) to calculate
CeN*. The zircon Ce anomalies calculated by this method, together with the Eu anomalies (EuN/EuN*) of the Yanshanian granites suggest that those related to Cu–(Au)–Mo mineralization have the highest oxygen fugacity (fO2) (proxied by CeN/CeN* and EuN/EuN*), followed by those related to Cu−Pb–Zn mineralization, and finally by those related to W–Sn, W and Sn mineralization. Furthermore, within a particular Cu–(Au)–Mo mineral district, the ore-related granites have higher fO2 (CeN/CeN*) than the barren ones. Besides, although reducing magmas generally favor Sn mineralization, some of the most-reduced granites in the Sn mineral districts are actually barren, which indicates that an extreme drop of fO2 could inhibit Sn mineralization. Keywords: Yanshanian granites; magma fertility (Cu–Mo–Au, Pb–Zn, Sn), zircon Ce-Eu anomalies; oxygen fugacity; South China.
1. Introduction It has been widely accepted that the redox state of magmas exerts a major control on the mineralization potential (Lehmann, 1982; Ballard et al., 2002; Liang et al., 2009; Ayati et al., 2013; Dilles et al., 2015; Shen et al., 2015; Richard, 2015; Sun et al., 2015; Li et al. 2017). Various methods have been used to evaluate the magmatic redox state, including (i) whole-rock Fe2+/Fe3+ ratios (Kress and Carmichael, 1989; Putirka, 2016), (ii) mineral reactions and equilibrium, and oxygen-barometer, e.g., for olivine, pyroxene, amphibole, sphene and apatite (Frost and Lindsley, 1992; Andersen et al., 1993; Ghiorso and Evans, 2008; Ridolfi et al., 2010), and (iii) biotite Fe2+/Fe3+ ratios (Eugster and
Wones, 1962; Wones and Eugster, 1965; Stone, 2000; Yavuz, 2003a and 2003b; Li et al. 2017). More recently, the zircon REE ratios, particularly EuN/EuN* and CeN/CeN* (N = chondrite-normalized), have been extensively used as proxies of magma oxygen fugacity for evaluating the mineralization potential of granitic rocks (Ballard et al., 2002; Blevin, 2004; Dilles et al., 2015; Richard, 2015; Shen et al., 2015; Sun et al., 2015; Lu et al., 2016; Gardiner et al., 2017). In one of our recent studies (Li et al., 2017), the compositions of biotite from various ore-related/-barren Yanshanian (Jurassic-Cretaceous) granites in South China were used to calculate the magma oxygen fugacity (fO2), covering the commodities of Cu–(Au)–Mo, Cu–Pb–Zn, and W–Sn–Nb–Ta (Hua et al., 2005; Zhang et al., 2006; Li et al., 2008; Shu et al., 2011; Feng et al., 2012; Li et al., 2012; Mao et al., 2013; Huang et al., 2014). We argued that there are systematic fO2 differences in the Cu–(Au)–Mo, Cu–Pb–Zn, W, Sn, and W–Sn ore-forming magmas. We also suggested that within a porphyry Cu–(Au)–Mo ore district, the ore-forming granites have higher fO2 than the barren ones (Li et al., 2017). Since biotite is susceptible to hydrothermal alteration, in this study we attempt to use the highly-resistate zircon REE chemistry to verify if the same systematic fO2 differences occur among different mineralization types, and between the ore-forming and barren granites. We proposed a modified method to calculate the Ce anomalies, since the La and Pr contents used by conventional calculations cannot be accurately analyzed in laboratories. Since South China is a world-class Sn–W metallogenic province, we also
expand the data compilation and analysis to cover Sn–W ore-related/barren granites.
2. Geological background and regional data compilation South China is composed of the Yangtze Block to the northwest and the Cathaysia Block to the southeast, separated by the Qin (Qinzhou)-Hang (Hangzhou) tectonic belt (Fig. 1; Gilder et al., 1991; Zhou and Li, 2000; Mao et al., 2013; Ding et al., 2015). Multiphase granitic intrusive events occurred in the Neoproterozoic, early Paleozoic (Caledonian), Triassic (Indosinian) and Jurassic-Cretaceous (Yanshanian) (Li et al., 2003; Wang et al., 2006; Zhou et al., 2006; Li and Li, 2007; Zhu et al., 2014). Among these four major generations of granites in South China, the Yanshanian ones are the most widespread and distributed mainly in the Cathaysia Block and the Qin-Hang belt. There is a progressive coastward migration trend of granitic magmatism from the early to late Yanshanian orogeny (Zhou et al., 2000; Zhou et al., 2006; Jiang et al., 2009). Four major types of ore metal assemblages are present in the Yanshanian granite-related mineralization, including porphyry Cu–(Au)–Mo, porphyry-related Cu–Pb–Zn, W, and Sn ore deposits (Mao et al., 2013; Fig. 1b). Some granites are related to both W and Sn deposits, and they are referred to as W–Sn-related granites in this study (i.e., Qianlishan granite). Major porphyry Cu–(Au)–Mo deposits include Dexing, Yongping, Dabaoshan, Yuanzhuding and Luoboling (Fig. 1b). Porphyry-related Cu–Pb–Zn deposits are mainly distributed in southeastern Hunan, e.g., Baoshan, Shuikoushan and Tongshanling. Granite-related W deposits are mainly distributed in the
Nanling Mountains and northeastern Jiangxi, e.g., Dajishan, Piaotang, Taoxikeng and Yaogangxian (Fig. 1b). Granite-related Sn deposits are mainly distributed in the western Nanling Mountains and in the SE China coastal region, e.g., Guposhan, Furong, and Yanbei (Fig. 1b). Granites associated with porphyry Cu–(Au)–Mo mineralization were emplaced in ca. 170–145 Ma and 107–100 Ma, whereas those associated with porphyry Cu–Pb–Zn mineralization were emplaced in ca. 172–161 Ma. The W, W–Sn, and Sn ore-related granites were generally younger (ca. 163–80 Ma) (Fig. 1c). Besides, porphyry Mo deposits are also discovered in South China, e.g., Shizitou, Xiongjiashan, Yanglin and Chilu, yet no published zircon geochemical data are available (Meng et al., 2007; Zeng et al., 2013; Ni et al., 2016 a, b). Our study area covers a large part of South China, including western Zhejiang, Jiangxi, southern Hunan, eastern Guangxi, Guangdong and western Fujian (Fig. 1). Yanshanian granites associated with Sn-polymetallic deposits in western Guangxi and Yunnan are not included in this study due to the lack of zircon chemical/isotopic data. Twenty granite intrusions associated with different types of mineralization were included in this study (Supplementary Table 1 and Fig. 1). Three barren granites from Zijinshan, Dabaoshan and Tongcun were also included to compare with the Cu–(Au)–Mo ore-related granites, and five barren granites (Ehu, Dadongshan, Xuehuapi, Jiufeng and Qinghu granites) were included to compare with Sn ore-related granites (Supplementary Table1).
3. Modified method for EuN/EuN* and CeN/CeN* calculation Both Eu and Ce have two valence states, i.e., Eu3+ and Eu2+, and Ce3+ and Ce4+. Eu3+ and Ce4+ are more compatible with Zr4+ in zircon than Eu2+ and Ce3+, respectively, and therefore an oxidizing condition favors the entering of Eu and Ce into the zircon crystal lattice. Thus, the EuN/EuN* and CeN/CeN* ratios (subscript N = chondrite-normalized; superscript * = trend value of the REE pattern) can be used as proxies of the magma oxygen fugacity (fO2). The EuN and CeN values are equal to Eu and Ce concentrations divided by chondrite normalizing values from McDonough and Sun (1995). EuN* is interpolated from the neighboring elements of Sm and Gd, i.e., (SmN × GdN)1/2. As for the calculation of CeN*, the conventional way is similar to that for EuN*, i.e., through interpolation of the neighboring elements La and Pr. This method, however, produces results with large errors because the La and Pr contents are typically very low in zircon (10s−100s of ppb; Hoskin and Schalteggar, 2003), and occasionally below the LA-ICP-MS detection limit. Furthermore, the zircon La and Pr contents may be significantly influenced by tiny mineral inclusions (Liu et al., 2010, Qiu et al., 2013; Dilles et al., 2015; Gardiner et al., 2017; Loader et al., 2017). Loader et al. (2017) proposed a different method to calculate CeN* by extrapolating from Sm and Nd rather than between La and Pr. Although the calculated CeN* values yielded less uncertainty (as the zircon Sm and Nd contents are higher), they are nevertheless also dependent on only two elements.
Hence, here we proposed a new CeN* calculation method by quadratic curve-fitting using all REEs except La and Pr (due to their low concentrations) and Eu and Ce (as their multi-valence can induce deviation from the partition coefficient – radii diagram). Modeling trace element partition coefficients using the lattice strain model can reveal the partitioning behavior in mineral/melt systems (Ballard et al., 2002). This method is based on the fact that the partition coefficients of elements with the same charge tend to result in a smooth curve (parabolic relationship) and are related to the square of the ionic radii (Onuma et al., 1968; Brice, 1975; Thomas et al., 2002; Qiu et al., 2014a, b). The method is illustrated in Figure 2, using the zircon data from a Yanshanian granite at Yuanzhuding in Guangdong (Zhong et al., 2013) as an example. In this example, the log values of all REE elements (except La, Pr, Ce and Eu) show a well-defined parabolic correlation with their respective ionic radii, and the estimated log (CeN*) (which lie on the regression line) is markedly different from that estimated from the interpolation between La and Pr (Fig. 2). This regression method is used for all zircon data in this study, and the values calculated using the conventional La–Pr interpolation method are aslo listed in Supplementary Table 2 and illustrated in Figures 3, 4 and 5 for comparison.
4. Results 4.1. Zircon EuN/EuN* and CeN/CeN* values for the different types of ore-related granites in South China As discussed earlier, Yanshanian granites in South China may be classified into five
groups based on metal assemblages: Cu–(Au)–Mo, Cu–Pb–Zn, W, W–Sn and Sn. The CeN/CeN* and EuN/EuN* ratios of zircon from the Yanshanian granites associated with these different types of mineralization are shown in Fig. 3, and the data is summarized in Table 1. Zircon EuN/EuN* values from the Cu–(Au)–Mo ore-related granites are high (0.06 to 1.04, avg. 0.63), which overlap partially with those related to the Cu–Pb–Zn (0.01 to 0.60, avg. 0.38) and W mineralization (0.02 to 1.54, avg. 0.21) (Fig. 3). The zircon EuN/EuN* values from the W–Sn (0.01 to 0.51, avg. 0.1) and Sn (0.01 to 0.23, avg. 0.08) ore-related granites are lower than those related to the Cu–(Au)–Mo mineralization (Fig. 3; Table 1). Ranges of zircon CeN/CeN* values from the different types of ore-related granites overlap with one another regardless of the calculation methods used (Figs. 3a and c). The conventional approach yielded CeN/CeN* values of 5 to 1023 (avg. 177) for the Cu–(Au)–Mo ore-related granites, 1 to 392 (avg. 19) for the Cu–Pb–Zn ore-related granites, 1 to 77 (avg. 15) for the W ore-related granites, 1 to 234 (avg. 39) for the W–Sn ore-related granites, and 1 to 191 (avg. 21) for the Sn ore-related granites (Table 1; Fig. 3b). However, the new method yielded a more confined range of CeN/CeN* values (Figs. 3c and d), and revealed higher values (despite some overlapping) for the Cu–(Au)–Mo (8 to 793, avg. 116) and Cu–Pb–Zn (7 to 1135, avg. 238) ore-related granites than the W–Sn (2 to 414, avg. 67), W (5 to 176, avg. 49) and Sn (1 to 194, avg. 40) ore-related granites (Table 1; Fig. 3). Notably, the new method can calculate the CeN/CeN* values for the analysis with low La and Pr contents (below the detection limit), hence, the number of
CeN/CeN* values produced is much higher than that produced by the convention method (Figs. 3a and c). It is notable that the redox trend reflected by EuN/EuN* ratios is different from that by CeN/CeN* ratios. While both EuN/EuN* and CeN/CeN* ratios of zircon indicate that Cu–(Au)–Mo-related granites are the most oxidizing among all the granites examined, the CeN/CeN* ratios of zircon appear to suggest that W related and W–Sn-related granites have similar redox state, in contrast with the estimation from EuN/EuN* ratios (Table 1 and Fig. 3).
4.2. Zircon EuN/EuN* and CeN/CeN* difference for Cu–(Au)–Mo fertile and barren granites As shown in Figure 4, the zircon EuN/EuN* values from the Cu–(Au)–Mo ore-related/-barren granites can be broadly divided into two groups based on EuN/EuN* = 0.5. Compared to the EuN/EuN* values of the Cu–(Au)–Mo ore-related granites (0.06 to 1.04; avg. 0.63), those of their barren counterparts are significantly lower (0.02 to 0.67, avg. 0.29). For the related granites, the CeN/CeN* values calculated with the conventional method (5 to 1023, avg. 177) is broadly similar to those calculated with the new method (7 to 1185, avg. 238), but the CeN/CeN* range of the barren granites yielded by the new method (4 to 560, avg. 144) is much narrower than those yielded by the conventional method (2 to 1095, avg. 190). Thus, the new method gives much clearer discrimination between Cu–(Au)–Mo ore-related and barren granites (Table 1; Fig. 4).
4.3. Zircon EuN/EuN* and CeN/CeN* difference for Sn fertile and barren granites As shown in Figure 5, the EuN/EuN* values from both the Sn ore-related (0.01 to 0.23, avg. 0.08) and barren (0.01 to 0.52, avg. 0.1) granites are low and hardly distinguishable. For the CeN/CeN* values calculated with the conventional method, distinction between ore-related granites (1 to 191, avg. 21) versus barren ones (1 to 124, avg. 8) are also ambiguous (Table 1). As shown in Fig. 5a, the CeN/CeN* ratios of zircons from Sn-related granites and barren granites largely overlap. CeN/CeN* values calculated using La–Pr interpolation method range from 1 to 191 (averaging 21) for the ore-bearing granite, and from 1 to 124 (averaging 8) for the barren granite (Table 1; Fig. 5b). In contrast with Fig. 5a, the plots in Fig. 5b can be divided into two groups by CeN/CeN* ratios clearly, and most data points of the Sn- bearing granites were located in upper area (CeN/CeN* > 10). The results estimated by the new approach range from 1 to 194 (averaging 41) for the ore-bearing granites, and from 1 to 351 (averaging 28) for the barren granites (Table 1; Fig. 5b), indicating the ore-related granites contain higher CeN/CeN* values than those of the barren granites.
5. Discussion 5.1. Comparison of the new and conventional CeN/CeN* calculation methods In this study, published data compilation and analysis revealed that 20% of zircon
data contain La and Pr contents close to or below the detection limit (e.g., Dabaoshan), rendering the conventional method useless in evaluating the magma redox state for these zircons (Table 1 and Supplementary Table 2). In many cases, the new method also yielded a more confined CeN/CeN* range than the conventional method, thus enabling better discrimination among ore-related granites of the various deposit types, and between the ore-related and the barren granites of a particular deposit type. We suggest that this improvement is partly attributed to the non-reliance of the zircon La and Pr contents, which can seldomly be accurately measured by LA-ICP-MS and are susceptible to contamination by melt or apatite inclusions (which are commonly La-Pr rich) (Ballard et al., 2002; Wang et al., 2013). Besides, the REE3+ substitution into zircon is best achieved by the REEs with the closest ionic size to Zr4+, therefore favoring HREE substitution. The steady ionic size decrease with increasing atomic number for REEs results in the steady increase of chondrite-normalized concentrations in zircon (Onuma et al., 1968; Blundy and Wood, 1994; Burnham and Berry, 2012; Loader et al., 2017). As shown in Figure 2, over several orders of magnitude for REE elements from La to Lu (except for Ce and Eu), commonly fall off the increase trend. This suggests that the MREEs (Middle rare earth elements) and HREEs (Heavy rare earth elements) can be determined more precisely than LREEs (Light rare earth elements). Therefore, we consider that our new method is more robust, and can produce more calculated CeN/CeN* value than the conventional one.
5.2. Implications for granite-related polymetallic ore formation 5.2.1. Ore deposit type discrimination South China is famous for hosting a wide variety of metal deposits, especially for Sn–W, Cu–Mo–Au, and Pb–Zn (Mao et al., 2013). In a recent study (Li et al., 2017), we used biotite composition from granites to reveal that magma fO2 likely played a major role in determining what kinds of deposits would be formed. Similar conclusion has been reached in this study from the zircon CeN/CeN* and EuN/EuN* values. In the zircon CeN/CeN* vs. EuN/EuN* plot for the different types of ore-related granites (Fig. 3), the Cu–(Au)–Mo ore-related granites contain relatively restricted zircon CeN/CeN* and higher EuN/EuN* values (i.e., more oxidizing). The Sn ore-related granites contain lower zircon CeN/CeN* and EuN/EuN* values. It is widely agreed that high magma fO2 is important to inhibit early sulfide crystallization and thereby promote the concentration of Cu–Au in the residual fluids/melts, thus facilitating porphyry Cu–Au mineralization (Liang et al., 2009; Sillitoe, 2010; Sun et al., 2013b, 2015; Richard, 2015; Gardiner et al., 2017). In contrast, low fO2 is beneficial for Sn mineralization (Linnel et al., 1996; Jiang et al., 2006; Wang et al., 2011). Linnen et al. (1996) suggested that Sn occurs dominantly as Sn2+ under low fO2 and as Sn4+ under high fO2. Sn4+ can replace Ti4+ and find accommodation in early crystallized mafic minerals such as magnetite, and thus behaving as a compatible element. However, at low fo2, Sn mainly exists as Sn2+, whose large ionic radius leads to the enrichment in the residual melt and eventually in hydrothermal fluids (Linnen et al., 1996). Hence, low fo2 is beneficial for Sn mineralization.
Notably, Cu–Pb–Zn related granite zircons have medium CeN/CeN* values and a wide EuN/EuN* range (Figs. 3c and d). However, CeN/CeN* ratios of zircon appear to suggest that W related and W-Sn-related granites have similar redox state. Unlike Cu, the elements of W, Pb and Zn could be incompatible regardless of their redox state, i.e., W, Pb and Zn mineralization can occur under high or low fO2 (Mengason et al., 2011; Qiu et al., 2014). This is supported by many findings that both I-type (oxidized) or S-type (reduced) granitic magmas could form W and Pb–Zn deposits (e.g., Li et al. 2012; Niu et al. 2017; Zhong et al., 2017). Also, we have observed that the EuN/EuN* ratios of zircon appear to suggest a different redox state which is in contrast with the estimation from CeN/CeN* ratios in Cu–Pb–Zn, W and W-Sn bearing granites (Table 1 and Fig. 3). In order to further evaluate the function of CeN/CeN* and EuN/EuN* values for mineralization styles, we plot the average zircon EuN/EuN* versus CeN/CeN* values for the each deposit selected in this study. In the average zircon EuN/EuN* vs. CeN/CeN* plot (Fig. 6), the Cu-mineralization related zircons define a relatively restricted field with high CeN/CeN* and EuN/EuN*, whilst the Sn-mineralization related zircons have lower CeN/CeN* and EuN/EuN*. Since Eu/Eu* is sensitive to both redox and fractionation, it may also be used as an index of magma fractionation (Ballard et al., 2002; Thomas et al., 2002; Dilles et al., 2015; Richards, 2015; Sun et al., 2015; Shen et al., 2015). The zircon Ce/Ce* vs. Eu/Eu* plot could therefore be used to reflect the differences in magma redox and fractionation states of the various magmatic-hydrothermal deposit types.
5.2.2. Implications for Yanshanian Cu–(Au)–Mo and Sn mineralization in South China In this study, it can be seen that most of the Yanshanian Cu–(Au)–Mo ore-related granites are more oxidized than their barren counterparts (Figs. 4a and c), indicating that higher fO2 is important for the mineralization. This is consistent with the results from most studies about porphyry Cu mineralization worldwide, which argued that higher fO2 could inhibit early sulfide fractionation and thus concentrate the metals into the residual fluids for mineralization (Richards, 2003, 2015; Sun et al., 2015; Li et al. 2017). As proposed by some authors (e.g., Ballard et al., 2002; Dilles et al., 2015), zircon EuN/EuN* >0.4 is characteristic of many ore-forming magmas, in the case of Mesozoic South China, the fertile granites commonly have EuN/EuN* > 0.5. As discussed above, the Yanshanian Sn ore-related granites in South China are characterized by low CeN/CeN* values (fO2) (Fig. 5), which is in agreement with many previous studies on individual Sn deposits in the region (Huang et al., 2014; Gardiner et al., 2017; Li et al., 2017; Song et al., 2017, 2018; Wei et al., 2017, 2018). However, some highly-reduced granites are Sn barren (Fig. 5), which suggests that extreme reducing condition may not be favorable for Sn mineralization. The actual cause is yet to be fully understood, but it may be partly led by the fact that Sn2+ is more mobile than Sn4+ in hydrothermal fluids (Linnen et al., 1996), that is to say, Sn2+ is much more soluble (transported by Cl-rich fluids) and thus less likely to precipitate to form Sn ores.
It is noteworthy that the zircon EuN/EuN* ratios, no matter from Sn fertile or infertile granites, are low (Figs. 5a and c). This suggests that the EuN/EuN* ratios in these granites are mainly controlled by plagioclase fractionation (which can be influenced by the magma water content) instead of the magma redox state.
6. Conclusions (1) We propose a new calculation method for Ce anomalies, which is performed by fitting of MREEs and HREEs (except Eu). This method avoids the issue of inaccurate laboratory La–Pr concentration measurement, which produces large errors to the conventional (La–Pr interpolation) Ce anomaly calculation approach. (2) Granites related to the Yanshanian Cu–(Au)–Mo mineralization in South China have the highest CeN/CeN* and EuN/EuN* ratios, followed by those related to the Cu−Pb–Zn mineralization, and then by those related to the W, W–Sn and Sn mineralization. This trend reflects the change of ore metal assemblage with decreasing oxygen fugacity of the mineral system. (3) In a particular granite-related Cu–(Au)–Mo mineral district in South China, the zircon CeN/CeN* and EuN/EuN* ratios of the fertile granites are markedly higher than those of the infertile ones. This suggests that oxidizing magmas promote Cu–(Au)–Mo mineralization. In South China, the fertile vs. infertile discrimination boundary is determined to be EuN/EuN* = 0.5. (4) In a particular granite-related Sn mineral district in South China, the zircon CeN/CeN*
ratios of the fertile granites are generally lower than those of the infertile granites, yet some granites with very low CeN/CeN* are barren. This suggests that although low oxygen fugacity generally favors Sn mineralization, further reduction in the hydrothermal system may actually inhibit the mineralization. The zircon EuN/EuN*ratios of the fertile and infertile granites are largely indistinguishable, suggesting that the ratios are controlled mainly by plagioclase fractionation.
Acknowledgments This study was financially supported by the NSFC (No. 418030401) and the China Scholarship Council Fund (No. 201406380063). We would like to thank Prof. Guoxiang Chi for the fruitful discussion and suggestions. We appreciate the constructive comments and suggestions by the editor and two anonymous reviewers, with which the paper was greatly improved.
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Figure captions Fig. 1. (a) Sketch tectonic map of China. (b) Simplified geologic map, showing the distribution of Yanshanian granites in South China and the ore deposits covered in this study (modified from Mao et al., 2013; Qiu et al., 2013). (c) Age histogram of the
granitic intrusions covered in this study.
Fig. 2. Quadratic curve-fitting between lnDi and function of radii for the REEs of the Yuanzhuding granite (average value calculated from Zhong et al., 2013).
Fig. 3. (a) CeN/CeN* vs. EuN/EuN* plot and (b) CeN/CeN* diagram, where CeN* is calculated by the conventional La-Pr interpolation method; (c) CeN/CeN* vs. EuN/EuN* plot and (d) CeN/CeN* diagram, where CeN* is calculated by our new MREE-HREE fitting method. Data of Yanshanian granites in South China are from Supplementary Table 2.
Fig. 4. (a) CeN/CeN* vs. EuN/EuN* diagram, where CeN* is calculated by the conventional La-Pr interpolation method; (b) CeN/CeN* vs. EuN/EuN* plot, where CeN* is calculated by our
new
MREE-HREE
fitting
method.
Data
of
Yanshanian
Cu-(Au)-Mo
ore-related/barren granites in South China are from Supplementary Table 2.
Fig. 5. (a) CeN/CeN* vs. EuN/EuN* diagram, where CeN* is calculated by the conventional La-Pr interpolation method; (b) CeN/CeN* vs. EuN/EuN* plot, where CeN* is calculated by our new MREE-HREE fitting method. Data of Yanshanian Sn ore-related/barren granites in South China are from Supplementary Table 2.
Fig. 6. Plot of average zircon EuN/EuN* vs. CeN/CeN*.
Captions for tables Table 1. Range and mean values of EuN/EuN* and CeN/CeN* from zircons in granites associated with different types of mineralization and Cu–Mo–Au and Sn barren granites.
Supplementary Table 1. Yanshanian granites and related deposits from South China analyzed in this study.
Supplementary Table 2. Zircon compositions, including the EuN/EuN* and CeN/CeN* ratios calculated by the conventional and new methods.
Table 1 Range and mean values of EuN/EuN* and CeN/CeN* from zircons in granites associated with different types of mineralization and Cu–Mo–Au and Sn barren granites.
Sample Granite
Eu/Eu* Mean
CeN/CeN*a
n=
CeN/CeN*b
n=
min–max
Mean
min–max
Cu–Mo–Au bearing granite 0.63
0.06–1.04 223
167
5–1023
314
238
7–1185
Cu–Pb–Zn bearing granite 0.38
0.01–0.60 119
19
1–392
120
116
8–793
W bearing granite
0.21
0.02–1.54 47
15
1–77
47
49
5–176
W–Sn bearing granite
0.1
0.01–0.51 157
39
1–234
193
67
2–414
Sn bearing rock
0.08
0.01–0.23 66
22
1–191
83
41
1–194
Cu–Mo–Au barren granite 0.29
0.02–0.67 51
190
2–1095
54
144
4–560
Sn barren granite
0.02–0.52 62
8
1–124
80
28
1–351
0.1
Mean min–max
a
CeN/CeN* was calculated by La–Pr method; b CeN/CeN* was estimated by Linear Regression.
Highlights
We compiled and compared zircon REE data from ore-related/barren Yanshanian granites in South China.
A new method to calculate zircon Ce anomalies is proposed. Oxidizing and reducing magmas promote Cu-(Au)-Mo and Sn-related mineralization, respectively.
In South China, the fertile vs. infertile discrimination boundary is EuN/EuN* = 0.5. Very low oxygen fugacity may inhibit Sn mineralization in some cases.
Li et al. Fig. 6
S0169-1368(18)31022-9 https://doi.org/10.1016/j.oregeorev.2019.103105 OREGEO 103105
To appear in:
Ore Geology Reviews
Received Date: Revised Date: Accepted Date:
12 December 2018 18 May 2019 29 August 2019
Please cite this article as: X. Li, Q. Gao, H. Song, J. Zhang, C-K. Lai, Discriminating ore fertile and barren granites using zircon Ce and Eu anomalies – Perspective from late Mesozoic (Yanshanian) granites in South China, Ore Geology Reviews (2019), doi: https://doi.org/10.1016/j.oregeorev.2019.103105
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Discriminating ore fertile and barren granites using zircon Ce and Eu anomalies – Perspective from late Mesozoic (Yanshanian) granites in South China Xingyuan Lia, b*, Quanzhou Gaoa*, Hao Songc, Jingru Zhangd, Chun-Kit Laie, f a. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China b. Department of Geology, University of Regina, Regina, S4S 0A2, Canada c. Chengdu University of Technology, Chengdu, 610059, China d. Guangdong Province Academic of Environmental Science, Guangzhou, 510045, China e. Faculty of Science, Universiti Brunei Darussalam, Gadong, Brunei Darussalam f. ARC Centre of Excellence in Ore Deposits (CODES), University of Tasmania, Hobart, Tasmania, Australia
*
Corresponding
authors:
X.
Li
([email protected])
and
Q.
Gao
([email protected]) Abstract: Redox conditions are widely considered to be important to magma fertility, and have been estimated using different proxies, notably the biotite Fe3+/Fe2+ ratios and zircon Ce and Eu anomalies. In this research, we compiled a large number of zircon REE data from both the fertile (Cu–(Au)–Mo, Cu−Pb–Zn, W–Sn, W and Sn) and barren Yanshanian (Jurassic-Cretaceous) granites from South China to test whether zircon REE compositional differences can differentiate various deposit types and discriminate fertile intrusions from barren ones. We propose a modified method to calculate Ce anomalies (CeN/CeN*, chondrite-normalized) using all MREEs and HREEs (except Eu) to calculate
CeN*. The zircon Ce anomalies calculated by this method, together with the Eu anomalies (EuN/EuN*) of the Yanshanian granites suggest that those related to Cu–(Au)–Mo mineralization have the highest oxygen fugacity (fO2) (proxied by CeN/CeN* and EuN/EuN*), followed by those related to Cu−Pb–Zn mineralization, and finally by those related to W–Sn, W and Sn mineralization. Furthermore, within a particular Cu–(Au)–Mo mineral district, the ore-related granites have higher fO2 (CeN/CeN*) than the barren ones. Besides, although reducing magmas generally favor Sn mineralization, some of the most-reduced granites in the Sn mineral districts are actually barren, which indicates that an extreme drop of fO2 could inhibit Sn mineralization. Keywords: Yanshanian granites; magma fertility (Cu–Mo–Au, Pb–Zn, Sn), zircon Ce-Eu anomalies; oxygen fugacity; South China.
1. Introduction It has been widely accepted that the redox state of magmas exerts a major control on the mineralization potential (Lehmann, 1982; Ballard et al., 2002; Liang et al., 2009; Ayati et al., 2013; Dilles et al., 2015; Shen et al., 2015; Richard, 2015; Sun et al., 2015; Li et al. 2017). Various methods have been used to evaluate the magmatic redox state, including (i) whole-rock Fe2+/Fe3+ ratios (Kress and Carmichael, 1989; Putirka, 2016), (ii) mineral reactions and equilibrium, and oxygen-barometer, e.g., for olivine, pyroxene, amphibole, sphene and apatite (Frost and Lindsley, 1992; Andersen et al., 1993; Ghiorso and Evans, 2008; Ridolfi et al., 2010), and (iii) biotite Fe2+/Fe3+ ratios (Eugster and
Wones, 1962; Wones and Eugster, 1965; Stone, 2000; Yavuz, 2003a and 2003b; Li et al. 2017). More recently, the zircon REE ratios, particularly EuN/EuN* and CeN/CeN* (N = chondrite-normalized), have been extensively used as proxies of magma oxygen fugacity for evaluating the mineralization potential of granitic rocks (Ballard et al., 2002; Blevin, 2004; Dilles et al., 2015; Richard, 2015; Shen et al., 2015; Sun et al., 2015; Lu et al., 2016; Gardiner et al., 2017). In one of our recent studies (Li et al., 2017), the compositions of biotite from various ore-related/-barren Yanshanian (Jurassic-Cretaceous) granites in South China were used to calculate the magma oxygen fugacity (fO2), covering the commodities of Cu–(Au)–Mo, Cu–Pb–Zn, and W–Sn–Nb–Ta (Hua et al., 2005; Zhang et al., 2006; Li et al., 2008; Shu et al., 2011; Feng et al., 2012; Li et al., 2012; Mao et al., 2013; Huang et al., 2014). We argued that there are systematic fO2 differences in the Cu–(Au)–Mo, Cu–Pb–Zn, W, Sn, and W–Sn ore-forming magmas. We also suggested that within a porphyry Cu–(Au)–Mo ore district, the ore-forming granites have higher fO2 than the barren ones (Li et al., 2017). Since biotite is susceptible to hydrothermal alteration, in this study we attempt to use the highly-resistate zircon REE chemistry to verify if the same systematic fO2 differences occur among different mineralization types, and between the ore-forming and barren granites. We proposed a modified method to calculate the Ce anomalies, since the La and Pr contents used by conventional calculations cannot be accurately analyzed in laboratories. Since South China is a world-class Sn–W metallogenic province, we also
expand the data compilation and analysis to cover Sn–W ore-related/barren granites.
2. Geological background and regional data compilation South China is composed of the Yangtze Block to the northwest and the Cathaysia Block to the southeast, separated by the Qin (Qinzhou)-Hang (Hangzhou) tectonic belt (Fig. 1; Gilder et al., 1991; Zhou and Li, 2000; Mao et al., 2013; Ding et al., 2015). Multiphase granitic intrusive events occurred in the Neoproterozoic, early Paleozoic (Caledonian), Triassic (Indosinian) and Jurassic-Cretaceous (Yanshanian) (Li et al., 2003; Wang et al., 2006; Zhou et al., 2006; Li and Li, 2007; Zhu et al., 2014). Among these four major generations of granites in South China, the Yanshanian ones are the most widespread and distributed mainly in the Cathaysia Block and the Qin-Hang belt. There is a progressive coastward migration trend of granitic magmatism from the early to late Yanshanian orogeny (Zhou et al., 2000; Zhou et al., 2006; Jiang et al., 2009). Four major types of ore metal assemblages are present in the Yanshanian granite-related mineralization, including porphyry Cu–(Au)–Mo, porphyry-related Cu–Pb–Zn, W, and Sn ore deposits (Mao et al., 2013; Fig. 1b). Some granites are related to both W and Sn deposits, and they are referred to as W–Sn-related granites in this study (i.e., Qianlishan granite). Major porphyry Cu–(Au)–Mo deposits include Dexing, Yongping, Dabaoshan, Yuanzhuding and Luoboling (Fig. 1b). Porphyry-related Cu–Pb–Zn deposits are mainly distributed in southeastern Hunan, e.g., Baoshan, Shuikoushan and Tongshanling. Granite-related W deposits are mainly distributed in the
Nanling Mountains and northeastern Jiangxi, e.g., Dajishan, Piaotang, Taoxikeng and Yaogangxian (Fig. 1b). Granite-related Sn deposits are mainly distributed in the western Nanling Mountains and in the SE China coastal region, e.g., Guposhan, Furong, and Yanbei (Fig. 1b). Granites associated with porphyry Cu–(Au)–Mo mineralization were emplaced in ca. 170–145 Ma and 107–100 Ma, whereas those associated with porphyry Cu–Pb–Zn mineralization were emplaced in ca. 172–161 Ma. The W, W–Sn, and Sn ore-related granites were generally younger (ca. 163–80 Ma) (Fig. 1c). Besides, porphyry Mo deposits are also discovered in South China, e.g., Shizitou, Xiongjiashan, Yanglin and Chilu, yet no published zircon geochemical data are available (Meng et al., 2007; Zeng et al., 2013; Ni et al., 2016 a, b). Our study area covers a large part of South China, including western Zhejiang, Jiangxi, southern Hunan, eastern Guangxi, Guangdong and western Fujian (Fig. 1). Yanshanian granites associated with Sn-polymetallic deposits in western Guangxi and Yunnan are not included in this study due to the lack of zircon chemical/isotopic data. Twenty granite intrusions associated with different types of mineralization were included in this study (Supplementary Table 1 and Fig. 1). Three barren granites from Zijinshan, Dabaoshan and Tongcun were also included to compare with the Cu–(Au)–Mo ore-related granites, and five barren granites (Ehu, Dadongshan, Xuehuapi, Jiufeng and Qinghu granites) were included to compare with Sn ore-related granites (Supplementary Table1).
3. Modified method for EuN/EuN* and CeN/CeN* calculation Both Eu and Ce have two valence states, i.e., Eu3+ and Eu2+, and Ce3+ and Ce4+. Eu3+ and Ce4+ are more compatible with Zr4+ in zircon than Eu2+ and Ce3+, respectively, and therefore an oxidizing condition favors the entering of Eu and Ce into the zircon crystal lattice. Thus, the EuN/EuN* and CeN/CeN* ratios (subscript N = chondrite-normalized; superscript * = trend value of the REE pattern) can be used as proxies of the magma oxygen fugacity (fO2). The EuN and CeN values are equal to Eu and Ce concentrations divided by chondrite normalizing values from McDonough and Sun (1995). EuN* is interpolated from the neighboring elements of Sm and Gd, i.e., (SmN × GdN)1/2. As for the calculation of CeN*, the conventional way is similar to that for EuN*, i.e., through interpolation of the neighboring elements La and Pr. This method, however, produces results with large errors because the La and Pr contents are typically very low in zircon (10s−100s of ppb; Hoskin and Schalteggar, 2003), and occasionally below the LA-ICP-MS detection limit. Furthermore, the zircon La and Pr contents may be significantly influenced by tiny mineral inclusions (Liu et al., 2010, Qiu et al., 2013; Dilles et al., 2015; Gardiner et al., 2017; Loader et al., 2017). Loader et al. (2017) proposed a different method to calculate CeN* by extrapolating from Sm and Nd rather than between La and Pr. Although the calculated CeN* values yielded less uncertainty (as the zircon Sm and Nd contents are higher), they are nevertheless also dependent on only two elements.
Hence, here we proposed a new CeN* calculation method by quadratic curve-fitting using all REEs except La and Pr (due to their low concentrations) and Eu and Ce (as their multi-valence can induce deviation from the partition coefficient – radii diagram). Modeling trace element partition coefficients using the lattice strain model can reveal the partitioning behavior in mineral/melt systems (Ballard et al., 2002). This method is based on the fact that the partition coefficients of elements with the same charge tend to result in a smooth curve (parabolic relationship) and are related to the square of the ionic radii (Onuma et al., 1968; Brice, 1975; Thomas et al., 2002; Qiu et al., 2014a, b). The method is illustrated in Figure 2, using the zircon data from a Yanshanian granite at Yuanzhuding in Guangdong (Zhong et al., 2013) as an example. In this example, the log values of all REE elements (except La, Pr, Ce and Eu) show a well-defined parabolic correlation with their respective ionic radii, and the estimated log (CeN*) (which lie on the regression line) is markedly different from that estimated from the interpolation between La and Pr (Fig. 2). This regression method is used for all zircon data in this study, and the values calculated using the conventional La–Pr interpolation method are aslo listed in Supplementary Table 2 and illustrated in Figures 3, 4 and 5 for comparison.
4. Results 4.1. Zircon EuN/EuN* and CeN/CeN* values for the different types of ore-related granites in South China As discussed earlier, Yanshanian granites in South China may be classified into five
groups based on metal assemblages: Cu–(Au)–Mo, Cu–Pb–Zn, W, W–Sn and Sn. The CeN/CeN* and EuN/EuN* ratios of zircon from the Yanshanian granites associated with these different types of mineralization are shown in Fig. 3, and the data is summarized in Table 1. Zircon EuN/EuN* values from the Cu–(Au)–Mo ore-related granites are high (0.06 to 1.04, avg. 0.63), which overlap partially with those related to the Cu–Pb–Zn (0.01 to 0.60, avg. 0.38) and W mineralization (0.02 to 1.54, avg. 0.21) (Fig. 3). The zircon EuN/EuN* values from the W–Sn (0.01 to 0.51, avg. 0.1) and Sn (0.01 to 0.23, avg. 0.08) ore-related granites are lower than those related to the Cu–(Au)–Mo mineralization (Fig. 3; Table 1). Ranges of zircon CeN/CeN* values from the different types of ore-related granites overlap with one another regardless of the calculation methods used (Figs. 3a and c). The conventional approach yielded CeN/CeN* values of 5 to 1023 (avg. 177) for the Cu–(Au)–Mo ore-related granites, 1 to 392 (avg. 19) for the Cu–Pb–Zn ore-related granites, 1 to 77 (avg. 15) for the W ore-related granites, 1 to 234 (avg. 39) for the W–Sn ore-related granites, and 1 to 191 (avg. 21) for the Sn ore-related granites (Table 1; Fig. 3b). However, the new method yielded a more confined range of CeN/CeN* values (Figs. 3c and d), and revealed higher values (despite some overlapping) for the Cu–(Au)–Mo (8 to 793, avg. 116) and Cu–Pb–Zn (7 to 1135, avg. 238) ore-related granites than the W–Sn (2 to 414, avg. 67), W (5 to 176, avg. 49) and Sn (1 to 194, avg. 40) ore-related granites (Table 1; Fig. 3). Notably, the new method can calculate the CeN/CeN* values for the analysis with low La and Pr contents (below the detection limit), hence, the number of
CeN/CeN* values produced is much higher than that produced by the convention method (Figs. 3a and c). It is notable that the redox trend reflected by EuN/EuN* ratios is different from that by CeN/CeN* ratios. While both EuN/EuN* and CeN/CeN* ratios of zircon indicate that Cu–(Au)–Mo-related granites are the most oxidizing among all the granites examined, the CeN/CeN* ratios of zircon appear to suggest that W related and W–Sn-related granites have similar redox state, in contrast with the estimation from EuN/EuN* ratios (Table 1 and Fig. 3).
4.2. Zircon EuN/EuN* and CeN/CeN* difference for Cu–(Au)–Mo fertile and barren granites As shown in Figure 4, the zircon EuN/EuN* values from the Cu–(Au)–Mo ore-related/-barren granites can be broadly divided into two groups based on EuN/EuN* = 0.5. Compared to the EuN/EuN* values of the Cu–(Au)–Mo ore-related granites (0.06 to 1.04; avg. 0.63), those of their barren counterparts are significantly lower (0.02 to 0.67, avg. 0.29). For the related granites, the CeN/CeN* values calculated with the conventional method (5 to 1023, avg. 177) is broadly similar to those calculated with the new method (7 to 1185, avg. 238), but the CeN/CeN* range of the barren granites yielded by the new method (4 to 560, avg. 144) is much narrower than those yielded by the conventional method (2 to 1095, avg. 190). Thus, the new method gives much clearer discrimination between Cu–(Au)–Mo ore-related and barren granites (Table 1; Fig. 4).
4.3. Zircon EuN/EuN* and CeN/CeN* difference for Sn fertile and barren granites As shown in Figure 5, the EuN/EuN* values from both the Sn ore-related (0.01 to 0.23, avg. 0.08) and barren (0.01 to 0.52, avg. 0.1) granites are low and hardly distinguishable. For the CeN/CeN* values calculated with the conventional method, distinction between ore-related granites (1 to 191, avg. 21) versus barren ones (1 to 124, avg. 8) are also ambiguous (Table 1). As shown in Fig. 5a, the CeN/CeN* ratios of zircons from Sn-related granites and barren granites largely overlap. CeN/CeN* values calculated using La–Pr interpolation method range from 1 to 191 (averaging 21) for the ore-bearing granite, and from 1 to 124 (averaging 8) for the barren granite (Table 1; Fig. 5b). In contrast with Fig. 5a, the plots in Fig. 5b can be divided into two groups by CeN/CeN* ratios clearly, and most data points of the Sn- bearing granites were located in upper area (CeN/CeN* > 10). The results estimated by the new approach range from 1 to 194 (averaging 41) for the ore-bearing granites, and from 1 to 351 (averaging 28) for the barren granites (Table 1; Fig. 5b), indicating the ore-related granites contain higher CeN/CeN* values than those of the barren granites.
5. Discussion 5.1. Comparison of the new and conventional CeN/CeN* calculation methods In this study, published data compilation and analysis revealed that 20% of zircon
data contain La and Pr contents close to or below the detection limit (e.g., Dabaoshan), rendering the conventional method useless in evaluating the magma redox state for these zircons (Table 1 and Supplementary Table 2). In many cases, the new method also yielded a more confined CeN/CeN* range than the conventional method, thus enabling better discrimination among ore-related granites of the various deposit types, and between the ore-related and the barren granites of a particular deposit type. We suggest that this improvement is partly attributed to the non-reliance of the zircon La and Pr contents, which can seldomly be accurately measured by LA-ICP-MS and are susceptible to contamination by melt or apatite inclusions (which are commonly La-Pr rich) (Ballard et al., 2002; Wang et al., 2013). Besides, the REE3+ substitution into zircon is best achieved by the REEs with the closest ionic size to Zr4+, therefore favoring HREE substitution. The steady ionic size decrease with increasing atomic number for REEs results in the steady increase of chondrite-normalized concentrations in zircon (Onuma et al., 1968; Blundy and Wood, 1994; Burnham and Berry, 2012; Loader et al., 2017). As shown in Figure 2, over several orders of magnitude for REE elements from La to Lu (except for Ce and Eu), commonly fall off the increase trend. This suggests that the MREEs (Middle rare earth elements) and HREEs (Heavy rare earth elements) can be determined more precisely than LREEs (Light rare earth elements). Therefore, we consider that our new method is more robust, and can produce more calculated CeN/CeN* value than the conventional one.
5.2. Implications for granite-related polymetallic ore formation 5.2.1. Ore deposit type discrimination South China is famous for hosting a wide variety of metal deposits, especially for Sn–W, Cu–Mo–Au, and Pb–Zn (Mao et al., 2013). In a recent study (Li et al., 2017), we used biotite composition from granites to reveal that magma fO2 likely played a major role in determining what kinds of deposits would be formed. Similar conclusion has been reached in this study from the zircon CeN/CeN* and EuN/EuN* values. In the zircon CeN/CeN* vs. EuN/EuN* plot for the different types of ore-related granites (Fig. 3), the Cu–(Au)–Mo ore-related granites contain relatively restricted zircon CeN/CeN* and higher EuN/EuN* values (i.e., more oxidizing). The Sn ore-related granites contain lower zircon CeN/CeN* and EuN/EuN* values. It is widely agreed that high magma fO2 is important to inhibit early sulfide crystallization and thereby promote the concentration of Cu–Au in the residual fluids/melts, thus facilitating porphyry Cu–Au mineralization (Liang et al., 2009; Sillitoe, 2010; Sun et al., 2013b, 2015; Richard, 2015; Gardiner et al., 2017). In contrast, low fO2 is beneficial for Sn mineralization (Linnel et al., 1996; Jiang et al., 2006; Wang et al., 2011). Linnen et al. (1996) suggested that Sn occurs dominantly as Sn2+ under low fO2 and as Sn4+ under high fO2. Sn4+ can replace Ti4+ and find accommodation in early crystallized mafic minerals such as magnetite, and thus behaving as a compatible element. However, at low fo2, Sn mainly exists as Sn2+, whose large ionic radius leads to the enrichment in the residual melt and eventually in hydrothermal fluids (Linnen et al., 1996). Hence, low fo2 is beneficial for Sn mineralization.
Notably, Cu–Pb–Zn related granite zircons have medium CeN/CeN* values and a wide EuN/EuN* range (Figs. 3c and d). However, CeN/CeN* ratios of zircon appear to suggest that W related and W-Sn-related granites have similar redox state. Unlike Cu, the elements of W, Pb and Zn could be incompatible regardless of their redox state, i.e., W, Pb and Zn mineralization can occur under high or low fO2 (Mengason et al., 2011; Qiu et al., 2014). This is supported by many findings that both I-type (oxidized) or S-type (reduced) granitic magmas could form W and Pb–Zn deposits (e.g., Li et al. 2012; Niu et al. 2017; Zhong et al., 2017). Also, we have observed that the EuN/EuN* ratios of zircon appear to suggest a different redox state which is in contrast with the estimation from CeN/CeN* ratios in Cu–Pb–Zn, W and W-Sn bearing granites (Table 1 and Fig. 3). In order to further evaluate the function of CeN/CeN* and EuN/EuN* values for mineralization styles, we plot the average zircon EuN/EuN* versus CeN/CeN* values for the each deposit selected in this study. In the average zircon EuN/EuN* vs. CeN/CeN* plot (Fig. 6), the Cu-mineralization related zircons define a relatively restricted field with high CeN/CeN* and EuN/EuN*, whilst the Sn-mineralization related zircons have lower CeN/CeN* and EuN/EuN*. Since Eu/Eu* is sensitive to both redox and fractionation, it may also be used as an index of magma fractionation (Ballard et al., 2002; Thomas et al., 2002; Dilles et al., 2015; Richards, 2015; Sun et al., 2015; Shen et al., 2015). The zircon Ce/Ce* vs. Eu/Eu* plot could therefore be used to reflect the differences in magma redox and fractionation states of the various magmatic-hydrothermal deposit types.
5.2.2. Implications for Yanshanian Cu–(Au)–Mo and Sn mineralization in South China In this study, it can be seen that most of the Yanshanian Cu–(Au)–Mo ore-related granites are more oxidized than their barren counterparts (Figs. 4a and c), indicating that higher fO2 is important for the mineralization. This is consistent with the results from most studies about porphyry Cu mineralization worldwide, which argued that higher fO2 could inhibit early sulfide fractionation and thus concentrate the metals into the residual fluids for mineralization (Richards, 2003, 2015; Sun et al., 2015; Li et al. 2017). As proposed by some authors (e.g., Ballard et al., 2002; Dilles et al., 2015), zircon EuN/EuN* >0.4 is characteristic of many ore-forming magmas, in the case of Mesozoic South China, the fertile granites commonly have EuN/EuN* > 0.5. As discussed above, the Yanshanian Sn ore-related granites in South China are characterized by low CeN/CeN* values (fO2) (Fig. 5), which is in agreement with many previous studies on individual Sn deposits in the region (Huang et al., 2014; Gardiner et al., 2017; Li et al., 2017; Song et al., 2017, 2018; Wei et al., 2017, 2018). However, some highly-reduced granites are Sn barren (Fig. 5), which suggests that extreme reducing condition may not be favorable for Sn mineralization. The actual cause is yet to be fully understood, but it may be partly led by the fact that Sn2+ is more mobile than Sn4+ in hydrothermal fluids (Linnen et al., 1996), that is to say, Sn2+ is much more soluble (transported by Cl-rich fluids) and thus less likely to precipitate to form Sn ores.
It is noteworthy that the zircon EuN/EuN* ratios, no matter from Sn fertile or infertile granites, are low (Figs. 5a and c). This suggests that the EuN/EuN* ratios in these granites are mainly controlled by plagioclase fractionation (which can be influenced by the magma water content) instead of the magma redox state.
6. Conclusions (1) We propose a new calculation method for Ce anomalies, which is performed by fitting of MREEs and HREEs (except Eu). This method avoids the issue of inaccurate laboratory La–Pr concentration measurement, which produces large errors to the conventional (La–Pr interpolation) Ce anomaly calculation approach. (2) Granites related to the Yanshanian Cu–(Au)–Mo mineralization in South China have the highest CeN/CeN* and EuN/EuN* ratios, followed by those related to the Cu−Pb–Zn mineralization, and then by those related to the W, W–Sn and Sn mineralization. This trend reflects the change of ore metal assemblage with decreasing oxygen fugacity of the mineral system. (3) In a particular granite-related Cu–(Au)–Mo mineral district in South China, the zircon CeN/CeN* and EuN/EuN* ratios of the fertile granites are markedly higher than those of the infertile ones. This suggests that oxidizing magmas promote Cu–(Au)–Mo mineralization. In South China, the fertile vs. infertile discrimination boundary is determined to be EuN/EuN* = 0.5. (4) In a particular granite-related Sn mineral district in South China, the zircon CeN/CeN*
ratios of the fertile granites are generally lower than those of the infertile granites, yet some granites with very low CeN/CeN* are barren. This suggests that although low oxygen fugacity generally favors Sn mineralization, further reduction in the hydrothermal system may actually inhibit the mineralization. The zircon EuN/EuN*ratios of the fertile and infertile granites are largely indistinguishable, suggesting that the ratios are controlled mainly by plagioclase fractionation.
Acknowledgments This study was financially supported by the NSFC (No. 418030401) and the China Scholarship Council Fund (No. 201406380063). We would like to thank Prof. Guoxiang Chi for the fruitful discussion and suggestions. We appreciate the constructive comments and suggestions by the editor and two anonymous reviewers, with which the paper was greatly improved.
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Figure captions Fig. 1. (a) Sketch tectonic map of China. (b) Simplified geologic map, showing the distribution of Yanshanian granites in South China and the ore deposits covered in this study (modified from Mao et al., 2013; Qiu et al., 2013). (c) Age histogram of the
granitic intrusions covered in this study.
Fig. 2. Quadratic curve-fitting between lnDi and function of radii for the REEs of the Yuanzhuding granite (average value calculated from Zhong et al., 2013).
Fig. 3. (a) CeN/CeN* vs. EuN/EuN* plot and (b) CeN/CeN* diagram, where CeN* is calculated by the conventional La-Pr interpolation method; (c) CeN/CeN* vs. EuN/EuN* plot and (d) CeN/CeN* diagram, where CeN* is calculated by our new MREE-HREE fitting method. Data of Yanshanian granites in South China are from Supplementary Table 2.
Fig. 4. (a) CeN/CeN* vs. EuN/EuN* diagram, where CeN* is calculated by the conventional La-Pr interpolation method; (b) CeN/CeN* vs. EuN/EuN* plot, where CeN* is calculated by our
new
MREE-HREE
fitting
method.
Data
of
Yanshanian
Cu-(Au)-Mo
ore-related/barren granites in South China are from Supplementary Table 2.
Fig. 5. (a) CeN/CeN* vs. EuN/EuN* diagram, where CeN* is calculated by the conventional La-Pr interpolation method; (b) CeN/CeN* vs. EuN/EuN* plot, where CeN* is calculated by our new MREE-HREE fitting method. Data of Yanshanian Sn ore-related/barren granites in South China are from Supplementary Table 2.
Fig. 6. Plot of average zircon EuN/EuN* vs. CeN/CeN*.
Captions for tables Table 1. Range and mean values of EuN/EuN* and CeN/CeN* from zircons in granites associated with different types of mineralization and Cu–Mo–Au and Sn barren granites.
Supplementary Table 1. Yanshanian granites and related deposits from South China analyzed in this study.
Supplementary Table 2. Zircon compositions, including the EuN/EuN* and CeN/CeN* ratios calculated by the conventional and new methods.
Table 1 Range and mean values of EuN/EuN* and CeN/CeN* from zircons in granites associated with different types of mineralization and Cu–Mo–Au and Sn barren granites.
Sample Granite
Eu/Eu* Mean
CeN/CeN*a
n=
CeN/CeN*b
n=
min–max
Mean
min–max
Cu–Mo–Au bearing granite 0.63
0.06–1.04 223
167
5–1023
314
238
7–1185
Cu–Pb–Zn bearing granite 0.38
0.01–0.60 119
19
1–392
120
116
8–793
W bearing granite
0.21
0.02–1.54 47
15
1–77
47
49
5–176
W–Sn bearing granite
0.1
0.01–0.51 157
39
1–234
193
67
2–414
Sn bearing rock
0.08
0.01–0.23 66
22
1–191
83
41
1–194
Cu–Mo–Au barren granite 0.29
0.02–0.67 51
190
2–1095
54
144
4–560
Sn barren granite
0.02–0.52 62
8
1–124
80
28
1–351
0.1
Mean min–max
a
CeN/CeN* was calculated by La–Pr method; b CeN/CeN* was estimated by Linear Regression.
Highlights
We compiled and compared zircon REE data from ore-related/barren Yanshanian granites in South China.
A new method to calculate zircon Ce anomalies is proposed. Oxidizing and reducing magmas promote Cu-(Au)-Mo and Sn-related mineralization, respectively.
In South China, the fertile vs. infertile discrimination boundary is EuN/EuN* = 0.5. Very low oxygen fugacity may inhibit Sn mineralization in some cases.
Li et al. Fig. 6