Heavy mineral compositions in the northeast sandy lands and the provenance analysis
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摘要:
了解中国东北沙地的重矿物组成并探讨其在亚洲风尘系统研究中的作用具有重要意义。目前较少甚至缺乏的重矿物数据，这影响了对该地区风尘系统的深入理解。为分析东北沙地的重矿物组成并探究其在东北风尘系统研究中的作用，分别从浑善达克沙地（OD）、科尔沁沙地（HQ）、呼伦贝尔沙地（HL）和松嫩沙地（SN）采集了34个风成沙和河流沙样品并进行了分粒级处理（＜63 μm及63～125 μm）。同时，从哈尔滨荒山黄土剖面采集了4个末次冰期黄土样品（＜63 μm），利用Frequentist模型对哈尔滨黄土物源进行了定量重建。通过范围检验、非参数Kruskal-Wallis H检验和逐步判别函数分析（DFA），选择了7种重矿物及特征指数（蓝晶石、锐钛矿、石榴子石、辉石、钛铁矿（磁性）、稳定系数W 、GZi指数）作为最佳复合指标进行定量重建。结果表明，钛铁矿（磁性）为浑善达克沙地的特征矿物，磁铁矿为科尔沁沙地的特征矿物，氧化铁矿物（赤铁矿、褐铁矿）为呼伦贝尔沙地的特征矿物，氧化铁矿物（磁性）、绿帘石、角闪石和石榴子石为松嫩沙地的优势矿物；不同粒度组分的重矿物含量存在明显差异，极稳定矿物优先富集于细颗粒。哈尔滨黄土与松嫩和呼伦贝尔沙地（＜63 μm组分）具有相近的重矿物组成，而与浑善达克和科尔沁沙地有一定程度的差异。根据Frequentist模型，哈尔滨黄土的来源贡献依次为：松嫩沙地（44%～86%）、呼伦贝尔沙地（10%～39%）、科尔沁沙地（3%～16%）和浑善达克沙地（0～7%）。本研究突出了细颗粒沉积物的重矿物组成结合定量模型在风尘物源示踪研究中具有很好的应用前景。
Abstract:To understand the role of play in the Asian aeolian dust system, the heavy mineral composition of the sandy land in Northeast China was analyzed. At present, in-depth study in this regard is lacking, which limited our understanding of the wind dust system in this area. Therefore, 34 samples of eolian and fluvial sand were collected from Onqin Daga sandy land (OD), Horqin sandy land (HQ), Hulun Buir sandy land (HL), and Songnen sandy land (SN), from which two particle-size fractions (＜63 μm, 63～125 μm) were processed and analyzed. In addition, four loess samples (＜63 μm) of the Last Glacial Period were collected from a loess profile in barren mountains near Harbin. The source areas of the Harbin loess were reconstructed quantitatively in the Frequentist model. After the range test, non-parametric Kruskal-Wallis H-test, and stepwise discriminant function analysis, seven heavy minerals (kyanite, anatase, garnet, pyroxene, ilmenite etc), and four characteristic indices indicating anti-erosion ability and mother-rock composition were selected for quantitative reconstruction. Results show that ilmenite (magnetic) is the characteristic mineral of OD, magnetite is that of HQ, iron oxide minerals (hematite, limonite) are those of HL, and iron oxide minerals (magnetic), epidote, amphibole and garnet are dominant minerals of SN. The contents of heavy minerals in various grain size fractions are different, and highly stable minerals are preferentially enriched in fine particles. The Harbin loess and SN and HL (＜63 μm component) have similar heavy mineral assemblages, but different from OD and HQ to some extents. The result of the Frequentist model shows that the contribution rate to the source of supply to the Harbin's loess is SN (44%～86%), HL (10%～39%), HQ (3%～16%), and OD (0～7%). This study highlights that the heavy mineral composition of fine sediment combined with the quantitative model has a good application prospect in the source tracing of wind dust.
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表 1 中国东北部沙地与哈尔滨黄土重矿物统计
Table 1. Statistics of heavy minerals in sandy land of Northeast China and loess in Harbin
% 编号 锆石 磷灰石 蓝晶石 金红石 锐钛矿 白钛石 独居石 榍石 石榴子石 电气石 角闪石 绿帘石 钛铁矿 氧化铁矿物 辉石 磁铁矿 氧化铁矿物
（磁性）钛铁矿
（磁性）OD ＜63 μm 9.7 1.3 0 1.0 1.0 0.9 0.6 0.8 6.4 3.4 8.7 11.0 21.1 3.6 9.2 6.6 0 9.2 63～125 μm 4.0 0.4 0.2 1.7 0.1 1.9 1.2 4.3 27.4 0.9 5.0 20.2 20 5.7 0.8 1.5 0 0 HQ ＜63 μm 7.1 1.9 0 2.5 1.4 0.7 0.8 1.9 12.8 1.9 7.2 17.9 23.6 5.4 9.4 0.1 0 0 63～125 μm 3.9 0.1 0.2 1.5 0.1 2.3 1.9 4.8 34.6 1.6 2.5 21.2 16.1 2.7 1.1 0.6 0 0 HL ＜63 μm 8.9 1.2 0.1 1.1 0.3 1.5 0.3 1.8 10 1.2 9.4 13.2 21.4 13.6 0.4 7.2 0 0 63～125 μm 5.4 0.8 0.3 1.0 0.1 2.2 0.5 4.2 28.0 1.0 9.2 16.9 12.1 4.9 0.2 7.0 0 0 SN ＜63 μm 6.7 1.4 0 0.7 0.2 0.8 0.1 3.7 1.3 0.4 17.9 23.2 11.7 13.7 0.7 2.7 10 0 63～125 μm 1.6 1.0 0 0.2 0 0.7 0 4.8 0.9 0.1 28.2 27.7 7.3 13.0 1.3 0.9 6.6 0 ＜63 μm HB2 1.9 0 0 0.2 0.1 0.3 0 0.7 2.4 0.2 9.3 13.8 18.5 28.9 0 15.5 0 0 HB4 9.9 0.6 0 0.9 0.4 0.9 0 2.0 7.0 0.3 4.7 12.5 5.5 39.3 0.3 10.1 0 0 HB5 10 0.5 0 0.7 0.4 0.7 0 1.3 3.8 0.1 1.9 10.6 4.7 49.1 1.4 9.2 0 0 HB7 7.8 0.6 0 0.5 0.2 1.3 0 6.0 2.7 0 18.3 15.6 30.4 7.1 0 5.3 0 0 
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表 2 哈尔滨黄土定量物源混合贡献比例重建结果及标准差（SD）
Table 2. Quantitative reconstruction results and standard deviation of Harbin Loess provenance based on Frequentist model
样品号 浑善达克 科尔沁 呼伦贝尔 松嫩 GOF 比例/% SD 比例/% SD 比例/% SD 比例/% SD HB2 2 0.06 10 0.08 28 0.17 60 0.11 0.77 HB4 1 0.02 16 0.09 39 0.22 44 0.15 0.83 HB5 7 0.05 5 0.07 35 0.21 53 0.15 0.80 HB7 0 0.01 3 0.03 11 0.07 86 0.07 0.93
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