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Article

Sensitive Grain-Size Components of Last Glacial Loess on Chinese Loess Plateau and Their Response to East Asian Winter Monsoon

by
Qiansuo Wang
1,*,
Yougui Song
2,
Linqiong Duan
1 and
Jinchan Li
1
1
College of Land and Tourism, Luoyang Normal University, Luoyang 471934, China
2
State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061, China
*
Author to whom correspondence should be addressed.
Atmosphere 2023, 14(2), 304; https://doi.org/10.3390/atmos14020304
Submission received: 30 November 2022 / Revised: 5 January 2023 / Accepted: 1 February 2023 / Published: 3 February 2023
(This article belongs to the Special Issue Quaternary Westerlies and Monsoon Interaction in Asia)
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Abstract

:
Chinese loess provides the most detailed terrestrial records of paleoclimate changes. We employed the grain-size components of aeolian sediments to reconstruct the history of the East Asian winter monsoon (EAWM) on the Chinese Loess Plateau (CLP). Here, using the grain-size class vs. standard deviation method, we extracted the environmentally sensitive grain-size components of nine last glacial loess sections. The grain-size class vs. standard deviation diagrams showed two major grain-size components (fine and coarse), which varied from section to section. Material resource distances and post-depositional pedogenesis were the main factors affecting environmentally sensitive grain-size components. The coarse grain-size components of the Yulin, Baicaoyuan, Xifeng, and Luochuan sections were influenced by the transportation distance, while we attributed the fine grain-size components of the Weinan, Shaoling, Duanjiapo, and Chaona sections to pedogenesis. At the same time, the Mianchi section’s sensitive grain-size component was also coarse, and was affected by the local circulation from the nearby Yellow River terrace. Our comparison of sensitive grain-size components and EAWM revealed that the coarse grain-size components were progressively finer along with the EAWM from the northwest to the southeast on the CLP, and they can be regarded as the most suitable proxy indicator of the EAWM on the CLP.

1. Introduction

The near-continuous Quaternary loess-paleosol sequences and the Neogene red clay deposits on the CLP have provided important information about paleoclimatic and paleoenvironmental changes, with the global climate cooling since the Cenozoic Era and the appearance of inland drought [1,2,3,4,5,6,7,8,9,10,11,12,13,14]. The effects of alternations to loess-paleosol sequences on the CLP are well documented, including the changes brought by the East Asian monsoon (EAM) over the past 2.6 Myr [3,4,7,11,12,13,14,15,16]. The grain-size proxy exhibits high-quality information on the variability of the EAWM [3,4,7,8,10,14,15,16]. The grain size and thickness of the last glacial Malan loess (L1) exhibit a clear decreasing trend from northwest to southeast across the CLP [1,17,18,19,20,21,22,23,24,25,26,27], indicating that the EAWM weakened gradually.
Sedimental grain size is a widely used indicator for studying climatic changes and environmental evolution because of its close links to sedimental sources, transport dynamics, and depositional environments [22,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47]. Previous studies on the grain-size characteristics of modern dust and loess deposits suggested that the grain-size components of aeolian sediments have been employed to reconstruct the history of EAWM, which can provide important information about its provenance and changes in the sedimental environment [26,29,32,33,34,42,48,49,50,51]. A stronger EAWM results in a larger median size and higher coarse-fraction content of dust and loess samples [48,50,52,53,54,55]. Grain-size parameters, such as median and mean grain size, size ratio, and coarse-fraction content, are widely selected for reconstructions of winter monsoon variations [10,24,26,56,57,58]. Therefore, the grain sizes of loess/paleosol sequences are considered proxies for winter monsoon strength, which can be correlated with Northern and Southern Hemisphere proxy records [26,50].
The grain-size class standard deviation method permits easy identification of the grain-size intervals, with the largest variability along the sedimentary sequences [59]. Additionally, this method has been applied successfully in the research of loess [52,60], lake sediments [61], and marine deposits [53,55,59,62,63]. However, much less is known about the spatial variation characteristics of the environmentally sensitive grain-size components of the last glacial loess. Here, using the grain-size class standard deviation method, we performed an analysis of environmentally sensitive grain-size components from the last glacial loess on the CLP [64,65,66,67,68,69,70]. Our objective is to better determine which grain sizes of the loess deposits can be used to delineate variations in EAWM strength.

2. Materials and Methods

In our study, we logged nine last glacial loess sections in the CLP (Table 1), located at Yulin, Baicaoyuan, Xifeng, Luochuan, Chaona, Mianchi, Weinan, Duanjiapo, and Shaoling (Figure 1).
We prepared grain-size samples according to Lu et al.’s pretreatment method [71]. We first pretreated the dry bulk samples weighing 0.3–0.5 g with 30% hydrogen peroxide (H2O2) to remove organic matter, and then 10% hydrochloric acid (HCl) to remove calcium carbonate, which ensured that our results reflected the grain-size distribution of the siliciclastic loess fraction. We then suspended the treated samples in deionized water, dispersed with 10 mL 10% (NaPO3)6 solution, and sonicated and oscillated in an ultrasonic bath for 10 min to completely separate the fine particles. We measured the grain-size distributions using a Mastersizer 2000 which manufactured Malvern, Britain. Replicate analyses indicated that the mean grain size had an analytical error of <3%. We calculated the standard deviation with all samples for each 100-grain-sized class within a measurement range of 0.02–2000 μm with a 0.1 Φ interval. The standard deviations evidenced the sensitive degree of each grain-size component to the distance variation along the dust conveying direction. Here, we used the grain-size classes vs. the standard deviation method to identify the grain-size intervals with the most variability along a depositional sequence. We derived the percentage contents of samples for each grain-size level (generally divided into the 100-grain grade) from grain-size data. Additionally, we calculated the standard deviation from the grain-size data. We calculated the grain-size classes vs. standard deviation figures by taking the grain size as the X-axis and the standard deviation as the Y-axis, from which sensitive grain-size components could be clearly obtained.

3. Results

According to the grain-size records of the nine loess sections, the grain-size class vs. standard deviation values are displayed in Figure 2.
Figure 2 shows that two or three typical peaks are observed in the grain-size classes vs. standard deviation curves of nine sections. The grain-size variations in the aeolian sediments are controlled by many factors. The Yulin section shows two standard deviation peaks at 39.9 μm and 141.6 μm, with size-range boundaries of 71.0 μm (Figure 2a). However, the Baicaoyuan section also has the three standard deviation peaks at 0.4 μm, 16.0 μm, and 69.2 μm corresponding to size ranges which are <0.8 μm, 0.8–31.7 μm, and >31.7 μm (Figure 2b). The three standard deviation peaks appear in the Xifeng section as 0.6 μm, 11.9 μm, and 56.9 μm, corresponding to size ranges of <0.8 μm, 0.8–26.1 μm, and >26.1 μm, respectively (Figure 2c). The Luochuan section also has two standard deviation peaks at 14.2 μm and 56.4 μm, with size ranges of <28.3 μm and >28.3 μm, respectively (Figure 2d). For the Chaona section, there are three obvious peaks on the grain-size class vs. standard deviation curves, namely 3.9 μm, 14.1 μm, and 50.2 μm, which correspond to size ranges of <5.6 μm, 5.6–28.3 μm, and >28.3 μm, respectively (Figure 2e). The Mianchi section shows two standard deviation peaks at 39.9 μm and 87.5 μm, which have size-range boundaries of 56.4 μm (Figure 2f). The Weinan and Shaoling sections show two standard deviation peaks at 2.9 μm and 30.2 μm, and 12.6 μm and 35.6 μm, respectively, which have size-range boundaries of 6.6 μm and 17.8 μm, respectively (Figure 2g,i). The Duanjiapo section has many peaks on the grain-size class vs. standard deviation curves, with the two main peaks at 10.8 μm and 46.8 μm, which have size ranges of <21.4 μm and >21.4 μm, respectively (Figure 2h).
We obtained the fine and coarse sensitive grain-size components data by performing the Mann–Whitney U statistic. The Mann–Whitney U statistic process is as follows.
The computation of the Mann–Whitney U statistic begins by arbitrarily designating two samples as fine- and coarse-size groups. The data from the two groups are combined into one group (Table 2), with each data value retaining a group identifier of its original group. The pooled values are then ranked from 1 to n, with the smallest value being assigned a rank of 1. The fine and coarse grain sizes are designated as Group 1 and 2, respectively (Table 3). n1 is the amount of Group 1, while n2 is the amount of Group 2 (both are 9). We computed and designated the sum of the ranks of the values from Group 1 and 2 as W1 and W2, respectively. According to Table 2, W1 is 49 and W2 is 122.
We hypothesized that there were no differences between the fine and coarse grain-size components except for their average values. We tested that H0 had no difference the between fine and coarse grain size, whereas we tested that H1 had a difference between the fine and coarse grain size.
The U1 and U2 values are calculated as follows
U 1 = n 1 n 2 + n 1 ( n 1 + 1 ) 2 − W 1
U 2 = n 1 n 2 + n 2 ( n 2 + 1 ) 2 − W 2
where the values n and W have been obtained, and we calculated the Mann–Whitney U statistic statistics, in which U1 and U2 are 77 and 4, respectively. The Uα (α = 0.05) can be obtained from the U statistic schedule, which is 17 in this study. Because of U2 < Uα, the test rejects H0 and accepts H1. Our results show that the fine and coarse components have significant differences. The grain-size class vs. standard deviation curves of our selected loess sections display the coarse and fine sensitive grain-size components. The fine and coarse components presented the CLP’s spatial particle aggregation.

4. Discussion

4.1. Spatial Variations in Sensitive Grain-Size Components of Last Glacial Loess on CLP

The grain size of aeolian deposits is mainly affected by the source area, wind intensity, and weathering [10,17,29,38,56]. The loess deposits in the northern and northwestern regions have been relatively greater affected by the source area, and the weathering degree and pedogenesis have influenced and changed the particle-size distribution of the southeast loess [1,2,7,10,62]. According to the curves of the grain-size class vs. standard deviation (Figure 2), apart from the standard deviations of coarse and fine sensitive components in the Weinan and Mianchi sections being comparable, the sensitive coarse grain-size compositions of the Luochuan, Yulin, Xifeng, Shaoling, and Baicaoyuan sections have a higher standard deviation than the fine grain-size components. This indicated that the content of coarse particles can better reflect the sedimentary environment changes. The sensitive grain-size components of the Yulin, Baicaoyuan, Xifeng, and Luochuan sections were coarser, being more influenced by the distance from material resources, whereas the Weinan, Shaoling Duanjiapo, and Chaona sections were finer as they were more influenced by the weathering degree and pedogenesis. The sensitive grain-size components of the Mianchi section were also coarser, which may be affected by local circulation and the nearby Yellow River terrace.
Because the size ranges define the limits of classes, the grain-size component of the maximum peak belongs to the sand component, which with the intermediate peak belongs to the silt component [10,28,62], while the minimum peak mainly belongs to the silt component. Figure 2 shows that the sand component of the nine loess sections has the highest standard deviation value. Thus, the sand component displays a decreasing trend from northwest to southeast on the CLP. The silt component of the nine loess sections also decreases gradually. The clay and fine silt components from Xifeng, Luochuan, Shaoling, Weinan, Baicaoyuan, and Duanjiapo are mainly delivered in suspension transport by the high-level air current far away from the source area. Therefore, the fine grain-size component is not a suitable proxy indicator for the loess from the CLP. The standard deviation went to zero in the grain-size data of some loess sections, which mainly appeared in the superfine and coarse powder in the grain size-standard deviation curves (Figure 2). However, the superfine grain-size intervals were very small and divided into many more grain-size classes, which was one of the main reasons for the standard deviation to zero.
According to the two sensitive components, the coarse component in most loess sections has the largest standard deviation (Figure 2), with the highest degree of sensitivity for paleoclimatic changes, suggesting that this component is the most sensitive to the variation in source-to-sink distance. Thus, the coarse particle component is the most suitable proxy indicator of the last glacial loess.

4.2. The EAWM Implicated by Coarse Sensitive Grain-Size Component

Grain size is commonly used as a proxy for EAWM intensity, with higher values in glacial loess and lower values in interglacial paleosols [2,3,10,26,40,42]. Furthermore, magnetic susceptibility (MS) is also commonly used for EASM intensity, with the loess and paleosols layers showing lower and higher MS values, respectively [3,72,73,74,75]. Therefore, in our study, we used mean grain size (MGS) and low-frequency MS. The coarse grain-size component and MGS from the selected loess sections have a decreasing trend from northwest to southeast on the CLP (Figure 3), indicating the EAWM’s gradually weakening trend.
To further explore the variations in the EAWM, we selected MGS and MS to study the spatial changes (Figure 4 and Figure 5). The results showed that the MGS decreased from the northwest to the southeast on the CLP (Figure 5a), whereas the MS increased from the northwest to the southeast (Figure 5b). This indicated that the EAWM intensity gradually weakened following the variations in MGS. At the same time, the EASM intensity gradually enhanced following the variations in MS. The decreased coarse grain size and increased fine grain size corresponded with the distance of the EAWM from the Asian high-pressure center and dust source. In addition, the fine grain-size components that were linked to pedogenesis were affected by the EASM’s rainfall.
Above all, the spatial variations in the coarse grain-size component of the last glacial loess can better reflect the evolution of EAWM on the CLP. We interpret the decreasing trend in grain size and coarse sensitive size component from northwest to southeast as gradually weakening from the EAWM. The sedimental grain size appears to be arranged from large to small in the northwest and southeast, respectively, which indicates that the sensitive coarse grain-size component is a sensitive proxy for the EAWM’s variability.

5. Conclusions

Using the grain-size class vs. standard deviation method, we extracted the environmentally sensitive grain-size components based on the grain size of the nine last glacial loess sections. Among the sensitive grain-size components, the coarse particle size in most loess sections has the highest standard deviation. It also has the most degree of sensitivity, suggesting that the coarse-particle component is the most sensitive to the variations in source-to-sink distance. The coarse grain-size components also have a decreasing trend from northwest to southeast on the CLP. Comparisons between the coarse grain-size component and mean grain size reveal that the coarse grain-size components decrease along with the weakening of the EAWM from the northwest to the southeast on the CLP, which can be regarded as a suitable proxy indicator of grain size and the EAWM on the CLP. More evidence regarding grain size is needed in the future to reflect the evolution process of the EAWM and atmospheric circulation.

Author Contributions

Funding acquisition, Q.W. and Y.S.; writing—original draft preparation, Q.W.; writing—review and editing, Y.S. and L.D.; visualization, J.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB26000000), the National Natural Science Foundation of China (Grant No. 41807287), and the Shandong Provincial Natural Science Foundation (No. ZR2017BD017).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets of this study are available from https://figshare.com/s/4320fb0983f7a5a47f91, accessed on 2 February 2023.

Acknowledgments

Many thanks to Junchao Dong for their field and lab assistance, and Xiaodong Miao for discussion. We are grateful for the two reviewers’ critical comments and suggestions.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Map showing location of loess sections (black spot) (a) on Chinese Loess Plateau (b). YL: Yulin; BCY: Baicaoyuan; XF: Xifeng; LC: Luochuan; CN: Chaona; MC: Mianchi; WN: Weinan; DJP: Duanjiapo; SL: Shaoling; EASM: East Asian summer monsoon; EAWM: East Asian winter monsoon.
Figure 1. Map showing location of loess sections (black spot) (a) on Chinese Loess Plateau (b). YL: Yulin; BCY: Baicaoyuan; XF: Xifeng; LC: Luochuan; CN: Chaona; MC: Mianchi; WN: Weinan; DJP: Duanjiapo; SL: Shaoling; EASM: East Asian summer monsoon; EAWM: East Asian winter monsoon.
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Figure 2. Grain-size classes vs. standard deviation curves of nine last glacial loess sections (a–i) on Chinese Loess Plateau.
Figure 2. Grain-size classes vs. standard deviation curves of nine last glacial loess sections (a–i) on Chinese Loess Plateau.
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Figure 3. Variations in coarse particle size by scatter plot (a) and bar graph (b) from nine last glacial loess sections.
Figure 3. Variations in coarse particle size by scatter plot (a) and bar graph (b) from nine last glacial loess sections.
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Figure 4. Variations in mean grain size (MGS; red) and magnetic susceptibility (MS; blue) of Yulin (a), Xifeng (b), and Weinan (c) loess sections in last glacial period. The gray area indicates last glacial loess.
Figure 4. Variations in mean grain size (MGS; red) and magnetic susceptibility (MS; blue) of Yulin (a), Xifeng (b), and Weinan (c) loess sections in last glacial period. The gray area indicates last glacial loess.
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Figure 5. Boxplots of mean grain size (MGS) (a) and magnetic susceptibility (MS) (b) (with percentiles 2.5, 25, 50, 75, 97.5%) from Yulin, Xifeng, and Weinan loess sections.
Figure 5. Boxplots of mean grain size (MGS) (a) and magnetic susceptibility (MS) (b) (with percentiles 2.5, 25, 50, 75, 97.5%) from Yulin, Xifeng, and Weinan loess sections.
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Table
Table 1. Nine last glacial loess sites on the Chinese Loess Plateau.
Table 1. Nine last glacial loess sites on the Chinese Loess Plateau.
SamplingSectionsSamplesLatitudeLongitudeAltitudeL1 ThicknessL1 MGS 1
SiteAbbreviations° N° Emmμm
YulinYL20038.271109.792119711.6062.75
BaicaoyuanBCY21036.218105.024183013.35 41.33
XifengXF20535.783107.623135211.80 29.41
LuochuanLC5635.752109.41610658.04 22.37
ChaonaCN20835.147107.22414646.18 21.32
MianchiMC13034.772111.7775357.12 24.87
WeinanWN28834.415109.5627878.20 18.62
DuanjiapoDJP20934.188109.2335935.00 18.41
ShaolingSL9134.138108.9654436.70 18.15
1 MGS is mean grain size.
Table
Table 2. Ranks of fine and coarse grain size from nine loess sections.
Table 2. Ranks of fine and coarse grain size from nine loess sections.
RanksGrain SizeRanksGrain Size
12.90 1039.80
210.80 1139.90
311.90 1246.80
412.60 1350.20
514.10 1456.40
614.20 1556.90
716.00 1669.20
830.20 1787.50
935.60 18141.60
Table
Table 3. Groups of fine and coarse grain size from nine loess sections.
Table 3. Groups of fine and coarse grain size from nine loess sections.
Group 1Group 2
Grain SizeRanksGrain SizeRanks
39.90 11141.80 18
16.00 769.20 16
11.90 356.90 15
14.20 656.40 14
14.10 550.20 13
39.80 1087.50 17
2.90 130.20 8
10.80 246.80 12
12.60 435.60 9
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Wang, Q.; Song, Y.; Duan, L.; Li, J. Sensitive Grain-Size Components of Last Glacial Loess on Chinese Loess Plateau and Their Response to East Asian Winter Monsoon. Atmosphere 2023, 14, 304. https://doi.org/10.3390/atmos14020304

AMA Style

Wang Q, Song Y, Duan L, Li J. Sensitive Grain-Size Components of Last Glacial Loess on Chinese Loess Plateau and Their Response to East Asian Winter Monsoon. Atmosphere. 2023; 14(2):304. https://doi.org/10.3390/atmos14020304

Chicago/Turabian Style

Wang, Qiansuo, Yougui Song, Linqiong Duan, and Jinchan Li. 2023. "Sensitive Grain-Size Components of Last Glacial Loess on Chinese Loess Plateau and Their Response to East Asian Winter Monsoon" Atmosphere 14, no. 2: 304. https://doi.org/10.3390/atmos14020304

APA Style

Wang, Q., Song, Y., Duan, L., & Li, J. (2023). Sensitive Grain-Size Components of Last Glacial Loess on Chinese Loess Plateau and Their Response to East Asian Winter Monsoon. Atmosphere, 14(2), 304. https://doi.org/10.3390/atmos14020304

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