1
2
[Geophysical Research Letters]
3
Supporting Information for
4
5
[Dolomite abundance in Chinese loess deposits: a new proxy of monsoon precipitation
intensity]
6
7
[Xianqiang Meng1, Lianwen Liu1, William Balsam2, Shilei Li1,Tong He1,Jun Chen1, Junfeng
Ji1*]
8
9
10
[1 Ministry of Education Key Laboratory of Surficial Geochemistry, School of Earth Sciences and Engineering,
Nanjing University, 163 Xianlindadao, Nanjing 210023, China; 2 Department of Earth Sciences, Dartmouth
College, Hanover, NH, 03755, USA]
11
12
13
14
15
16
Contents of this file
17
Introduction
18
Text S1
Figures S1 to S11
Tables S1 to S4
The supporting Information includes a method description text, nine figures and
19
three tables. The text S1 describes measuring method about dolomite and calcite. The
20
figures S1 to S9 include measurement of dolomite and calcite, relationship between
21
carbonate, MS and MAP, and conceptual models of dissolution phases of carbonate
22
minerals. The tables S1 to S3 exhibit measuring error of dolomite and carbonate and
23
dolomite and calcite mean content of each subunit in all eight sections.
24
25
Text S1: Quantification of dolomite and calcite by FTIR
26
In recent years carbonate minerals in the soil have been identified and quantified
27
by Fourier Transform infrared spectroscopy (FTIR) with a diffuse reflectance
28
attachment, which is a quick and relatively inexpensive method that is sensitive to
29
carbonate molecular vibration signal [Álvarez et al., 2012; He et al., 2012; Ji et al.,
30
2009; Legodi et al., 2001; Nguyen et al., 1991; Reeves Iii, 2010; Reig et al., 2002;
31
Tatzber et al., 2007]. We selected the absorption peaks from 2513-2522 cm-1 (for total
32
carbonate) and 2626 cm-1 (for dolomite) because they are free of interference from
33
other minerals in a non-carbonate soil matrix and the reflection peaks area is far
34
greater than other peaks (Figure S2). Because the peak 2626 cm-1 is easy to hide by
35
high calcite content, the calcite was completely removed from bulk sample by weak
36
acid. A series of condition experiments (Table S2) were designed to find a best
37
reaction condition under which calcite was removed completely and dolomite
38
remained unattacked. First, 0.5 g of sample was placed into a 50 ml centrifuge tube
39
with 45ml of 0.05, 0.1, 0.2 and 0.5 mole/L acetic acid when the total carbonate
40
content of bulk sample was about ≤ 8% (relative error (δ )= ± 24.43%)，8 - 14% (δ = ±
41
8.65%), 14 - 18% (δ = ± 7.45%) and ≥18% (δ = ± 10.51%) respectively (Table DR2),
42
and reacted for 30 minutes at room temperature based on a series of experiments.
43
Then, after the reaction each sample was centrifuged and washed once with deionized
44
water and dried for 24 hours at 45℃, and was determined by FTIR again. The
45
calibration equation of dolomite and total carbonate produced by add them to matrix
46
which removed carbonate completely using hydrochloric acid [Ji et al., 2009]. The
47
quantitative equations are y = 0.000972 x + 0.00217 (R2 = 0.996, RMSE = 0.13) for
48
dolomite and y = 0.0000996 x – 0.00261 (R2 = 0.995, RMSE = 0.72) for total
49
carbonate, where y and x are dolomite or total carbonate content and band area at
50
2626 or 2513 cm-1 respectively (Fig. S 2). Calcite content was obtained by subtracting
51
dolomite from total carbonate. We estimated the limit of detection in our loess matrix
52
was ≤ 0.22% for dolomite and was ≤ 0.13% for total carbonate because the
53
reflectance band area of 0.22% dolomite and 0.13% total carbonate were clear at 2626
54
cm-1 and 2513 cm-1 respectively (Figure S4).
55
Dolomite and protodolomite are also appear in soil. Protodolomite is defined as
56
those metastable single-phase rhombohedral carbonates which are imperfectly ordered.
57
Previous studies using XRD and SEM methods demonstrated that dolomite in
58
Chinese loess is composed of well-ordered crystals with d104 = 2.886 and a detrital
59
morphology under the SEM, whereas the protodolomite has a d104 value of about
60
2.902 (Fig. S5), is of pedogenic origin, has a low Mg/Ca (<0.6), and is only found in
61
the underlying late Neogene Red Clay [He et al., 2012; Li et al., 2007].
62
63
Additional references in supporting information “text S1”
64
Álvarez, J. L. G., M. J. T. Martínez, and M. A. Fernández (2012), Development of a
65
method for the quantitative analysis of urinary stones, formed by a mixture of
66
two components, using infrared spectroscopy, Clinical biochemistry, 45(7),
67
582-587, doi: 10.1016/j.clinbiochem.2012.02.008.
68
He, T., Y. Chen, W. Balsam, X. Sheng, L. Liu, J. Chen, and J. Ji (2012), Distribution
69
and origin of protodolomite from the late Miocene-Pliocene Red Clay Formation,
70
Chinese Loess Plateau, Geochemistry Geophysics Geosystems, 13, 1-17, doi:
71
10.1029/2012gc004039.
72
Ji, J., Y. Ge, W. Balsam, J. E. Damuth, and J. Chen (2009), Rapid identification of
73
dolomite using a Fourier Transform Infrared Spectrophotometer (FTIR): A fast
74
method for identifying Heinrich events in IODP Site U1308, Marine Geology,
75
258(1-4), 60-68, doi: 10.1016/j.margeo.2008.11.007.
76
Legodi, M., D. de Waal, J. Potgieter, and S. Potgieter (2001), Rapid determination of
77
CaCO< sub> 3</sub> in mixtures utilising FT—IR spectroscopy, Minerals
78
engineering, 14(9), 1107-1111, doi: 10.1016/S0892-6875(01)00116-9.
79
Li, G., J. Chen, Y. Chen, J. Yang, J. Ji, and L. Liu (2007), Dolomite as a tracer for the
80
source regions of Asian dust, Journal of Geophysical Research, 112(D17), 1-7,
81
doi: 10.1029/2007jd008676.
82
Nguyen, T., L. J. Janik, and M. Raupach (1991), Diffuse reflectance infrared Fourier
83
transform (DRIFT) spectroscopy in soil studies, Soil Research, 29(1), 49-67, doi:
84
10.1071/SR9910049
85
Porter, S. C., B. Hallet, X. Wu, and Z. An (2001), Dependence of Near-Surface
86
Magnetic Susceptibility on Dust Accumulation Rate and Precipitation on the
87
Chinese
88
10.1006/qres.2001.2224.
Loess
Plateau,
Quaternary
Research,
55(3),
271-283,
doi:
89
Reeves Iii, J. B. (2010), Near- versus mid-infrared diffuse reflectance spectroscopy
90
for soil analysis emphasizing carbon and laboratory versus on-site analysis:
91
Where are we and what needs to be done?, Geoderma, 158(1–2), 3-14, doi:
92
org/10.1016/j.geoderma.2009.04.005.
93
Reig, F. B., J. Adelantado, and M. Moya Moreno (2002), FTIR quantitative analysis
94
of calcium carbonate (calcite) and silica (quartz) mixtures using the constant
95
ratio method. Application to geological samples, Talanta, 58(4), 811-821.
96
Tatzber, M., M. Stemmer, H. Spiegel, C. Katzlberger, G. Haberhauer, and M.
97
Gerzabek (2007), An alternative method to measure carbonate in soils by FT-IR
98
spectroscopy,
99
10.1007/s10311-006-0079-5.
100
Environmental
Chemistry
Letters,
5(1),
9-12,
doi:
101
Figures S1 to S10
102
103
104
Figure S1. FTIR spectra of the bulk, HAOc- and HCl- treated loess sample (PL-115,
105
L1) and standard dolomite and calcite. Note that the shaded band shows the
106
absorption features at 2626 cm−1, which was used as a proxy for dolomite content.
107
108
109
110
Figure S2. Calibration equation of dolomite (a) and total carbonate contents (b) as a
111
function of reflectance band area at 2626 cm-1 and 2513 cm-1, respectively. Two
112
equations have a high R2 and low RMSE.
113
114
115
116
Figure S3. FTIR spectra of dolomite and total carbonate spiked samples, showing the
117
discrimination of the diagnostic FTIR absorption features of dolomite at 2626 cm-1 (a)
118
and total carbonate at 2513 cm-1 (b). Calcite represents total carbonate because calcite
119
is main carbonate minerals in Chinese loess and the area at 2513 cm-1 by adding
120
calcite is same as dolomite. Pure dolomite and calcite were added to splits of a non
121
carbonate sample to produce samples that contained different weight concentration of
122
dolomite and total carbonate.
123
124
125
Figure S4. Dolomite content change with longitude from west -east transects (a) and
126
latitude from north – south transects (b) in L1 and S1 units of the eight loess sections.
127
128
129
130
Figure S5. X-Ray diffraction patterns of dolomite in four loess-paleosol sections (HX,
131
XF, LC and CX) and showing that dolomite in loess is only detrital origin, not
132
pedogenic protodolomite. For main units and sub-units sample (S0, L1LL1, L1SS1,
133
L1LL2 and S1) are listed.
134
135
136
137
138
Figure S6. The grain size distribution of dolomite and calcite in typical L1 loess
samples from CX and HX sections.
139
140
Figure S7. The correlation between dolomite content and MS in the eight sections
141
studied. The low MS values correspond to high dolomite content and vice versa. Low
142
MS on the CLP has also been shown to correspond to low rainfall [Porter et al.,
143
2001].
144
145
146
147
148
Figure S8. Conceptual models concerning four dissolution phases of carbonate
149
minerals. The number 1, 2, 3 and 4 stand for the four dissolution phases of carbonate
150
minerals, respectively.
151
152
153
Figure S9. The four dissolution phases of carbonate minerals in the eight sections
154
from east to west (a) and from south to north (b). The dissolution phase in MIS 5c and
155
d can both be Phase 3 or 4, thus we labeled them as Phase 3 or 4 using dash lines and
156
question mark. The precipitation in MIS 5e is the strongest in all of MIS 5, thus the
157
MIS 5e at LT and BJ sections belong to phase 4
158
159
160
Figure S10. Relation of magnetic susceptibility and calcite content in
161
dolomite-contained samples (dissolution phase 1) (a) and non-dolomite samples
162
(dissolution phase 2) in eight sections.
163
164
165
Figure S11. Variations of dolomite (solid blue line) and calcite (solid red line) during
166
Holocene (S0) in the CR section (MAP=600 mm). SI: 10-8m3kg-1.
167
168
Tables S1 to S3
169
Table S1: Measuring error of instrument
XF-100
XF-200
Samples
Total carbonate content
1
8.72%
18.23%
2
7.93%
18.27%
3
8.52%
17.11%
4
8.80%
17.14%
5
8.52%
17.19%
6
8.89%
17.37%
7
8.48%
17.86%
Mean content
8.41%
17.41%
Standard deviation
0.13%
0.31%
Relative error (δ)
±1.55%
±1.78%
Measuring times
170
171
Table S2: The measuring and methodical error of dolomite quantification
XF-90
LC-660
XF-125
XF-200
Samples
Dolomite content
Concentration of acetic
0.05
0.1
0.2
0.5
30
30
30
30
1
0.56%
1.30%
1.30%
1.88%
2
0.54%
1.19%
1.18%
1.95%
3
0.44%
1.34%
1.22%
1.96%
4
0.41%
1.22%
1.12%
1.83%
5
0.51%
1.22%
1.25%
1.63%
6
0.46%
1.22%
1.25%
1.61%
7
0.50%
1.36%
1.15%
1.68%
Mean content
0.49%
1.26%
1.21%
1.79%
Standard deviation
0.28%
0.31%
0.29%
0.38%
Relative error (δ)
±24.43%
±8.65%
±7.45%
±10.51%
acid (mole/L)
Reaction time (minutes)
Measuring
times
172
173
174
Table S3: Mean dolomite and calcite contents in the eight sections
Samples Mean Dolomite Mean Calcite
Sections
Mean value of
Units or Subunits
NO.
content
content
MS(10–8m3kg–1)
LLL1(MIS2)
73
2.78%
16.67%
30.88
LSS1(MIS3)
69
2.43%
16.23%
30.03
LLL2(MIS4)
67
3.20%
16.13%
29.51
S1(MIS5)
68
1.95%
13.23%
33.10
Total
277
2.59%
15.59%
30.88
LLL1(MIS2)
21
1.35%
14.90%
50.32
LSS1(MIS3)
21
1.02%
12.24%
72.13
LLL2(MIS4)
15
1.43%
16.09%
40.40
S1(MIS5)
17
0.28%
7.17%
138.70
Total
74
1.01%
12.54%
75.39
LLL1(MIS2)
20
1.27%
15.77%
55.81
LSS1(MIS3)
22
0.92%
12.51%
80.95
LLL2(MIS4)
24
1.29%
14.61%
44.41
S1(MIS5)
36
0.08%
3.29%
139.86
Total
102
0.73%
9.90%
80.26
LLL1(MIS2)
22
0.83%
13.90%
78.16
Luochuan
LSS1(MIS3)
28
0.52%
12.48%
115.87
(LC)
LLL2(MIS4)
20
0.88%
13.64%
66.10
S1(MIS5)
21
0.00%
1.91%
209.30
Caoxian
(CX)
Pingliang
(PL)
Xifeng
(XF)
Total
91
0.49%
10.28%
117.36
LLL1(MIS2)
22
1.90%
13.74%
35.67
LSS1(MIS3)
32
1.75%
12.43%
42.52
LLL2(MIS4)
29
2.17%
12.70%
33.35
S1(MIS5)
36
0.59%
11.09%
81.73
Total
119
1.49%
12.61%
48.32
LLL1(MIS2)
25
1.40%
16.43%
56.98
LSS1(MIS3)
43
1.11%
12.23%
87.74
LLL2(MIS4)
34
1.48%
17.62%
44.12
S1(MIS5)
26
0.00%
3.03%
178.86
Total
128
0.98%
12.09%
91.93
LLL1(MIS2)
15
0.38%
5.84%
93.40
LSS1(MIS3)
14
0.36%
4.94%
118.92
Lingtai
LLL2(MIS4)
10
0.77%
9.50%
91.56
(LT)
S1(MIS5)
23
0.00%
0.32%
174.34
Total
62
0.24%
3.70%
119.56
LLL1(MIS2)
14
0.53%
14.79%
117.32
LSS1(MIS3)
21
0.00%
3.77%
177.50
LLL2(MIS4)
12
0.38%
10.11%
150.21
S1(MIS5)
15
0.00%
0.10%
238.96
Total
62
0.16%
5.62%
171.00
Huanxian
(HX)
Zhenyuan
(ZY)
Baoji
(BJ)
175
176
177
Table S4: Estimated the input dolomite concentration in glacial-interglacial cycle
178
from the mean grain size distribution data of L1 and S1 samples in western CX
179
section and eastern LC section. We assumed that the dolomite content of each grain
180
size in initial dust input is similar to that of CX-L1 (<30μm, 2.8%wt; 30-45μm,
181
5.2%wt; >45μm, 3.8%wt). Dolomite contents were calculated depended on dolomite
182
content in initial dust and mean percentage of grain size (<30, 30-45 and >45μm) in
183
western CX section and eastern LC section.
CX section
Dolomite
content in
assumed
initial
dust
(CX-L1)
Percen
tage
of
grain
size
Dolom
ite
conten
t
Percen
tage
of
grain
size
Dolom
ite
conten
t
Percen
tage
of
grain
size
Dolom
ite
conten
t
Percen
tage
of
grain
size
Dolom
ite
conten
t
<30μm
2.80%
60%
1.65%
75%
2.07%
70%
1.93%
79%
2.18%
30-45μm
5.20%
22%
1.16%
15%
0.79%
15%
0.79%
11%
0.58%
>45μm
3.80%
18%
0.68%
10%
0.38%
15%
0.57%
10%
0.38%
100%
3.50%
100%
3.24%
100%
3.29%
100%
3.14%
Grain
size
ranges
Total
184
L1
LC section
S1
L1
S1