Spatio-temporal variation of soil CO2 concentration in Loess Area of northwestern Shanxi Province, China

doi:10.3724/SP.J.1226.2022.2021-0013.

Abstract

Abstract:

CO₂ released by soil serves as an important link between terrestrial ecosystems and atmospheric CO₂, whose small changes may significantly affect the global carbon cycle. In order to reveal the spatio-temporal variations of CO₂ concentrations in deep loess, this paper takes Qingliangsi Gully watershed in northwestern Shanxi Province, China as an example to systematically study soil CO₂ concentration and its spatio-temporal variations and carbon sink significance under different watershed locations and different land use types. Results show that: (1) The release potential of the loess soil is larger in the depth range of 2 m, which is much more likely to be the CO₂ release area. (2) Grassland and forest are more advantageous in terms of soil microbial activity and soil carbon reserve compared with farmland. In addition, the change of land use type from farmland to grassland can increase soil organic carbon reserve, which is of far-reaching significance to the global carbon cycle. This is especially true in an area like the Loess Plateau with densely covered hills, gullies, and serious soil erosion in an area of 64×10⁴ km². (3) In the study area, the diurnal concentration of soil CO₂ at different depths shows a weak "high-low-high-low" trend from 08:00 to 07:00 next day; and in deep soil it has a lag time compared with the daily change of temperature, generally about 4-12 h, which may be caused largely by the more compact loess structure. It is worth pointing out that the Loess Plateau in China, with a thickness of the loess of tens to hundreds of meters, has the most abundant soil resources in the world, and also stores a large amount of terrestrial soil carbon, which carries the hope of promoting the research of global carbon cycle.

Key words: soil CO₂ concentration, China Loess Plateau, carbon sink function, release potential

TianJie Shao,ZhiPing Xu,LianKai Zhang,RuoJin Wang,JunJie Niu,MingYu Shao. Spatio-temporal variation of soil CO₂concentration in Loess Area of northwestern Shanxi Province, China[J].Sciences in Cold and Arid Regions, 2022, 14(3): 196-211.

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References 0

	Abdalla K, Mutema M, Chivenge P, et al., 2018. Grassland degradation significantly enhances soil CO₂ emission. Catena, 167: 284-292. DOI: 10.1016/j.catena.2018.05.010 . doi: 10.1016/j.catena.2018.05.010
	Arslan WSK, Waqar ZS, 2020. An empirical investigation between CO₂ emission, energy consumption, trade liberalization and economic growth: A case of Kuwait. Journal of Building Engineering, 28: 101104. DOI: 10.1016/j.jobe. 2019.101104 . doi: 10.1016/j.jobe. 2019.101104
	Assefa D, Rewald B, Sandén H, et al., 2017. Deforestation and land use strongly effect soil organic carbon and nitrogen stock in northwest Ethiopia. Catena, 153: 89-99. DOI: 10. 1016/j.catena.2017.02.003 . doi: 10. 1016/j.catena.2017.02.003
	Bezaye T, Rolf S, Kristin P, 2020. Potential for soil organic carbon sequestration in grasslands in east african countries: A review. Grassland Science, 66(3):135-144. DOI: 10.1111/grs.12267 . doi: 10.1111/grs.12267
	Bini G, Chiodini G, Cardellini C, et al., 2019. Diffuse emission of CO₂ and convective heat release at nisyros caldera (Greece). Journal of Volcanology and Geothermal Research, 376: 44-53. DOI: 10.1016/j.jvolgeores.2019.03.017 . doi: 10.1016/j.jvolgeores.2019.03.017
	Bloemendal J, Liu X, Sun Y, et al., 2008. An assessment of magnetic and geochemical indicators of weathering and pedogenesis at two contrasting sites on the Chinese Loess Plateau. Palaeogeography, Palaeoclimatology, Palaeoecololgy, 257(1-2): 152-168. DOI: 10.1016/j.palaeo.2007.09.017 . doi: 10.1016/j.palaeo.2007.09.017
	Chen Z, Li Y, Martinelli G, et al., 2020. Spatial and temporal variations of CO₂ emissions from the active fault zones in the capital area of China. Applied Geochemistry, 112: 1-10. DOI: org/10.1016/j.apgeochem.2019.104489 . doi: org/10.1016/j.apgeochem.2019.104489
	Choi Y, Kim D, Cho S, et al., 2019. Southeastern yellow sea as a sink for atmospheric carbon dioxide. Marine Pollution Bulletin, 149: 110550. DOI: 10.1016/j.marpolbul.2019.110550 . doi: 10.1016/j.marpolbul.2019.110550
	Courtois EA, Stahl C, Burban B, et al., 2018. Automatic high-frequency measurements of full soil greenhouse gas fluxes in a tropical forest. Biogeosciences, 16(3): 785-796. DOI: 10.5194/bg-16-785-2019 . doi: 10.5194/bg-16-785-2019
	Cui Y, Schubert BA, Jahren AH, 2020. A 23 m. y. record of low atmospheric CO₂. Geology, 48(9): 888-892. DOI: 10.1130/G47681.1 . doi: 10.1130/G47681.1
	Deng L, Shangguan ZP, Wu GL, et al., 2017. Effects of grazing exclusion on carbon sequestration in China's grassland. Earth-Science Reviews, 173: 84-95. DOI: 10.1016/j.earscirev.2017.08.008 . doi: 10.1016/j.earscirev.2017.08.008
	Dong X, Gao X, 2014. Long-term climate change: Interpretation of IPCC fifth assessment report. Progressus inquisitiones de mutatione climatis, 10(1): 56-59.
	Dummann W, Steinig S, Hofmann P, et al., 2020. The impact of early cretaceous gateway evolution on ocean circulation and organic carbon burial in the emerging south Atlantic and southern ocean basins. Earth Planetary Science Letters, 530: 115890. DOI: 10.1016/j.epsl.2019.115890 . doi: 10.1016/j.epsl.2019.115890
	Eickenscheidt N, Brumme R, 2013. Regulation of N₂O and NO_x emission patterns in six acid temperate beech forest soils by soil gas diffusivity, N turnover, and atmospheric NO_x concentrations. Plant Soil, 369(1-2): 515-529. DOI: 10.1007/s11104-013-1602-7 . doi: 10.1007/s11104-013-1602-7
	Erik OJ, Paal S, 2020. Summarizing an eulerian-lagrangian model for subsea gas release and comparing release of CO₂ with CH₄ . Applied Mathematatical Modelling, 79: 672-684. DOI: 10.1016/j.apm.2019.10.057 . doi: 10.1016/j.apm.2019.10.057
	Fu B, Wang S, Liu Y, et al., 2017. Hydrogeomorphic ecosystem responses to natural and anthropogenic changes in the Loess Plateau of China. Annual Review of Earth & Planetary Sciences, 45(1): 223-243. DOI: 10.1146/annurev-earth-063016-020552 . doi: 10.1146/annurev-earth-063016-020552
	Huang Y, Li Q, 2019. Karst biogeochemistry in China: Past, present and future. Environmental Earth Sciences, 78(15): 450. DOI: 10.1007/s12665-019-8400-3 . doi: 10.1007/s12665-019-8400-3
	IPCC, 2013. Climate Change Fifth Assessment Report: The Physical Science Basis. Cambridge, United Kingdom and New York, NY, USA. pp. 1535.
	Jevon FV, D'Amato AW, Woodall CW, et al., 2019. Tree basal area and conifer abundance predict soil carbon stocks and concentrations in an actively managed forest of northern New Hampshire, USA. Forest and Ecology Management, 451: 117534. DOI: 10.1016/j.foreco.2019.117534 . doi: 10.1016/j.foreco.2019.117534
	Jian J, Steele MK, Thomas Q, et al., 2018. Constraining estimates of global soil respiration by quantifying sources of variability. Global Change Biololgy, 24: 4143-4159. DOI: 10.1111/gcb.14301 . doi: 10.1111/gcb.14301
	Jiang Q, Qi Z, Xue L, et al., 2020. Assessing climate change impacts on greenhouse gas emissions, n losses in drainage and crop production in a subsurface drained field. Science of the Total Environment, 705: 135969. DOI: 10.1016/j.scitotenv.2019.135969 . doi: 10.1016/j.scitotenv.2019.135969
	Johnson G, Hicks N, Bond CE, et al., 2017. Detection and understanding of natural CO₂ releases in kwazulu-natal, South africa. Energy Procedia, 114: 3757-3763. DOI: 10.1016/j.egypro.2017.03.1505 . doi: 10.1016/j.egypro.2017.03.1505
	Joo SJ, Park SU, Park MS, et al., 2012. Estimation of soil respiration using automated chamber systems in an oak (quercus mongolica) forest at the nam-san site in seoul, Korea. Science of the Total Environment, 416: 400-409. DOI: 10.1016/j.scitotenv.2011.11.025 . doi: 10.1016/j.scitotenv.2011.11.025
	Larsen D, Bursi J, Waldron B, et al., 2020. Recharge pathways and rates for a sand aquifer beneath a loess-mantled landscape in western Tennessee, U.S.A. Journal of Hydrology: Regional Studies, 28: 100667. DOI: 10.1016/j.ejrh. 2020.100667 . doi: 10.1016/j.ejrh. 2020.100667
	Li Y, Zhao J, 2006. Soil CO₂ concentration under different artificial vegetations in south suburb of Xi'an. Journal of Desert Research, 26(6): 910-915. (in Chinese)
	Liang FY, Song LH, Wang J, 2003. Diurnal variation of soil CO₂ concentration and its relationship with soil CO₂ flux. Progress in Geography, 22: 170-175. (in Chinese)
	Liu Z, Dreybrodt W, Wang H, 2008. A possible important CO₂ sink by the global water cycle. Science Bulletin, 53(3): 402-407. DOI: 10.1007/s11434-008-0096-9 . doi: 10.1007/s11434-008-0096-9
	Liu Z, Zhao J, 2000. Contribution of carbonate rock weathering to the atmospheric CO₂ sink. Environment Geology, 39(9): 1053-1058. DOI: 10.1007/s002549900072 . doi: 10.1007/s002549900072
	McLaren AD, Anderson GH, Hopkins PD, 1984. Soil Biochemistry (Chinese edition). Beijing: Agriculture Press, pp. 490-492.
	Monteiro T, Kerr R, Orselli IBM, et al., 2020. Towards an intensified summer CO₂ sink behavior in the southern ocean coastal regions. Progress in Oceanography, 183: 102267. DOI: 10.1016/j.pocean.2020.102267 . doi: 10.1016/j.pocean.2020.102267
	Munir Q, Lean HH, Smyth R, 2020. CO₂ emissions, energy consumption and economic growth in the Asean-5 countries: A cross-sectional dependence approach. Energy Economics, 85: 104571. DOI: 10.1016/j.eneco.2019.104571 . doi: 10.1016/j.eneco.2019.104571
	Nelson DW, Sommers LE, Sparks DL, et al., 1996. Total carbon, organic carbon, and organic matter. Methods of Soil Analysis, 9: 961-1010. DOI: https://doi.org/10.2136/sssabookser5.3.c34 . doi: 10.2136/sssabookser5.3.c34
	Ni Y, Sun Z, Yi X, 2013. Influence of soluble carbon on N₂O and CO₂ emissions from soil of typical farm-land in north China. Journal of Soil and Water Conservation, 27(4): 222-227. (in Chinese)
	Otieno DO, K'Otuto GO, Jákli B, et al., 2010. Spatial heterogeneity in ecosystem structure and productivity in a moist Kenyan savanna. Plant Ecology, 212(5): 769-783. DOI: 10. 1007/s11258-010-9863-1 . doi: 10. 1007/s11258-010-9863-1
	Pacala SW, Hurtt GC, Baker D, et al., 2001. Consistent land- and atmosphere-based U.S. Carbon sink estimates. Science, 292(5525): 2316-2320. DOI: 10.1126/science.1057320 . doi: 10.1126/science.1057320
	Peng J, Wang S, Wang Q, et al., 2019. Distribution and genetic types of loess landslides in China. Journal of Asian Earth Sciences, 170: 329-350. DOI: 10.1016/j.jseaes.2018.11.015 . doi: 10.1016/j.jseaes.2018.11.015
	Phillips RL, Zak DR, Holmes WE, et al., 2002. Microbial community composition and function beneath temperate trees exposed to elevated atmospheric carbon dioxide and ozone. Oecologia, 131(2): 236-244. DOI: 10.1007/s00442-002-0868-x . doi: 10.1007/s00442-002-0868-x
	Shao T, Ma Y, Zhao J, et al., 2016. Vertical distribution of sand layer CO₂ concentration and its diurnal variation rules in alxa desert region, northwest China. Environmental Earth Sciences, 75(18): 1269. DOI: 10.1007/s12665-016-6083-6 . doi: 10.1007/s12665-016-6083-6
	Shen J, Zhang F, Mao D, 2001. Carbon cycling in rhizosphere micro-ecological system. Plant Natrition and Fertilizen Science, 7(2): 232-240. (in Chinese)
	Shen X, Su M, Sun T, et al., 2020. Net heterotrophy and low carbon dioxide emissions from biological processes in the yellow river estuary, China. Water Research, 171: 115457. DOI: 10.1016/j.watres.2019.115457 . doi: 10.1016/j.watres.2019.115457
	Song S, Wang ZA, Gonneea ME, et al., 2020. An important biogeochemical link between organic and inorganic carbon cycling: Effects of organic alkalinity on carbonate chemistry in coastal waters influenced by intertidal salt marshes. Geochimica ET Cosmochimica Acta, 275: 123-139. DOI: 10.1016/j.gca.2020.02.013 . doi: 10.1016/j.gca.2020.02.013
	Tao L, Zhao D, Zhang M, et al., 2013. Dynamic characteristics of the soil CO₂ and soil water chemistry, and their driving action on karstification. Tropical Geography, 33(5): 575-581. (in Chinese)
	Tiessen H, Cuevas E, Chacon P, 1993. The role of soil organic matter in sustaining soil fertility. Nature, 371: 783-785.
	Usman, Iskandar UP, Sugihardjo, et al., 2014. A systematic approach to source-sink matching for CO₂ eor and sequestration in south Sumatera. Energy Procedia, 63: 7750-7760. DOI: 10.1016/j.egypro.2014.11.809 . doi: 10.1016/j.egypro.2014.11.809
	Villarino SH, Studdert GA, Baldassini P, et al., 2016. Deforestation impacts on soil organic carbon stocks in the semiarid chaco region, Argentina. Science of the Total Environment, 575: 1056-1065. DOI: 10.1016/j.scitotenv.2016.09.175 . doi: 10.1016/j.scitotenv.2016.09.175
	Wagle P, Gowda PH, Neel JPS, et al., 2020. Integrating eddy fluxes and remote sensing products in a rotational grazing native tallgrass prairie pasture. Science of the Total Environment, 712: 136407. DOI: 10.1016/j.scitotenv. 2019.136407 . doi: 10.1016/j.scitotenv. 2019.136407
	Wang H, Wang S, Yu Q, et al., 2020. No tillage increases soil organic carbon storage and decreases carbon dioxide emission in the crop residue-returned farming system. Journal of Environment Management, 261: 110261. DOI: 10.1016/j.jenvman.2020.110261 . doi: 10.1016/j.jenvman.2020.110261
	Wang Z, He Y, Niu B, et al., 2020. Sensitivity of terrestrial carbon cycle to changes in precipitation regimes. Ecological Indicators, 113: 106223. DOI: 10.1016/j.ecolind.2020.106223 . doi: 10.1016/j.ecolind.2020.106223
	Wei W, Chen L, Fu B, et al., 2007. The effect of land uses and rainfall regimes on runoff and soil erosion in the semi-arid loess hilly area, China. Journal of Hydrology, 335(3-4): 247-258. DOI: 10.1016/j.jhydrol.2006.11.016 . doi: 10.1016/j.jhydrol.2006.11.016
	Wei Z, Wang JJ, Dodla SK, et al., 2020. Exploring anaerobic CO₂ production response to elevated nitrate levels in gulf of Mexico coastal wetlands: Phenomena and relationships. Science of the Total Environment, 709: 136158. DOI: 10.1016/j.scitotenv.2019.136158 . doi: 10.1016/j.scitotenv.2019.136158
	Williams MA, Rice C, Owensby CE, 2000. Carbon dynamics and microbial activity in tallgrass prairie exposed to elevated CO₂ for 8 years. Plant and Soil, 227(1-2): 127-137. DOI: 10.1023/A:1026590001307 . doi: 10.1023/A:1026590001307
	Wu CS, Sheen JD, Chen SY, et al., 2001. Feasibility of CO₂ fixation via artificial rock weathering. Industrial & Engineering Chemistry Research, 40(18): 3902-3905. DOI: 10. 1021/ie010222l . doi: 10. 1021/ie010222l
	Yang ZL, Wei YY, Fu GY, et al., 2020. Asymmetric effect of increased and decreased precipitation in different periods on soil and heterotrophic respiration in a semiarid grassland. Agricultural and Forest Meteorology, 291: 108039. DOI: 10.1016/j.agrformet.2020.108039 . doi: 10.1016/j.agrformet.2020.108039
	Yao P, Li X, Liu J, et al., 2018. The role of maize plants in regulating soil profile dynamics and surface emissions of nitrous oxide in a semiarid environment. Biology Fertility of Soils, 54(1): 119-135. 10.1007/s00374-017-1243-8 . doi: 10.1007/s00374-017-1243-8
	Yao, Yu K, Wang G, et al., 2019. Effects of soil erosion and reforestation on soil respiration, organic carbon and nitrogen stocks in an eroded area of southern China. Science of the Total Environment, 683: 98-108. DOI: 10.1016/j.scitotenv.2019.05.221 . doi: 10.1016/j.scitotenv.2019.05.221
	Yuan D, Zhang C, 2008. Karst dynamics theory in China and its practice. Acta Geoscientica Sinica, 29(3): 355-365. (in Chinese)
	Yun J, Jeong S, Ho C, 2020. Enhanced regional terrestrial carbon uptake over Korea revealed by atmospheric CO₂ measurements from 1999 to 2017. Global Change Biology, 26(6): 3368-3383. DOI: 10.1111/gcb.15061 . doi: 10.1111/gcb.15061
	Yusup Y, Alkarkhi AFM, Kayode JS, et al., 2018. Statistical modeling the effects of microclimate variables on carbon dioxide flux at the tropical coastal ocean in the southern south China sea. Dynamics of Atmospheres and Oceans, 84: 10-21. DOI: 10.1016/j.dynatmoce.2018.08.002 . doi: 10.1016/j.dynatmoce.2018.08.002
	Zang H, Li Y, Xue L, et al., 2018. The contribution of low temperature and biological activities to the CO₂ sink in Jiaozhou bay during winter. Journal of Marine Systems, 186: 37-46. DOI: 10.1016/j.jmarsys.2018.05.008 . doi: 10.1016/j.jmarsys.2018.05.008
	Zhang C, Zhao J, Yang X, 2008. Research on soil carbon dioxide density in different depths of the grassland. Journal of Shaanxi Normal University (Natural Science Edition), 36(6): 90-96. (in Chinese)
	Zhang H, Deng Q, Hui D, et al., 2019. Recovery in soil carbon stock but reduction in carbon stabilization after 56-year forest restoration in degraded tropical lands. Forest Ecology and Management, 441: 1-8. DOI: 10.1016/j.foreco.2019.03.037 . doi: 10.1016/j.foreco.2019.03.037
	Zhao J, Yuan D, Xi L, 2000. Research on the modern karst processes and absorbed amount of CO₂ in bahe river catchment of Xi'an. Quaternary Sciences, 20(4): 367-373. (in Chinese)

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Position (Quarter)	0-2 m Moisture content	Temperature (°C)			Soil type
Position (Quarter)	0-2 m Moisture content	0.5 m	1.0 m	2.0 m	Soil type
A1 (Spring)	12.75%±0.89%	12.37±0.78	9.36±1.25	7.66±0.78	Ma Lan loess
A2 (Spring)	12.95%±2.42%	12.55±1.41	8.82±1.28	7.58±1.35	Ma Lan loess
B (Spring)	12.22%±0.89%	13.30±0.71	9.95±0.74	8.43±0.64	Ma Lan loess
C (Spring)	10.18%±1.43%	15.88±0.39	12.50±0.40	11.83±0.44	Loess sediments deposited in river floodplains
A1 (Summer)	7.38%±1.29%	18.29±0.39	18.79±0.45	15.42±0.45	Ma Lan loess
A2 (Summer)	9.85%±2.93%	20.05±0.30	18.64±0.40	16.84±0.41	Ma Lan loess
B (Summer)	6.80%±0.94%	21.69±0.33	20.31±0.43	6.80±0.94	Ma Lan loess
C (Summer)	7.52%±3.20%	20.95±0.09	19.54±0.31	17.15±0.29	Loess sediments deposited in river floodplains
A1 (Autumn)	8.97%±2.45%	5.97±0.24	8.76±0.32	10.90±0.52	Ma Lan loess
A2 (Autumn)	10.87%±1.91%	5.47±0.23	6.80±0.33	10.03±0.29	Ma Lan loess
B (Autumn)	9.22%±2.20%	5.58±0.50	7.10±0.37	10.64±0.34	Ma Lan loess
C (Autumn)	7.83%±2.10%	6.18±0.20	9.03±0.37	10.81±0.74	Loess sediments deposited in river floodplains

Location	Depth (m)	Average value (×10^-4 m³/m³)	Range (×10^-4 m³/m³)	Variation coefficient
A1	2.0	91.0±5.6	83.0-101.0	6.1%
	1.0	61.7±7.4	50.0-75.0	11.9%
	0.5	48.1±3.9	40.0-54.0	8.1%
A2	2.0	176.1±15.0	148.0-204.0	8.5%
	1.0	131.4±16.0	96.0-150.0	12.2%
	0.5	73.6±7.1	56.0-83.0	9.6%
B	2.0	80.8±4.3	73.0-88.0	5.3%
	1.0	52.2±5.4	47.0-63.0	10.4%
	0.5	33.2±5.0	25.0-43.0	15.2%
C	2.0	89.0±5.0	74.0-94.0	5.0%
	1.0	80.1±4.2	68.0-86.0	5.3%
	0.5	68.9±2.9	63.0-74.0	4.3%

Location	Depth (m)	Average value (×10^-4 m³/m³)	Range (×10^-4 m³/m³)	Variation coefficient
A1	2.0	33.1±3.6	25.0-39.0	11.0%
	1.0	29.8±3.3	23.0-35.0	10.9%
	0.5	14.6±3.1	10.0-19.0	21.4%
A2	2.0	186.9±17.9	161.0-221.0	9.6%
	1.0	152.0±36.3	75.0-197.0	23.9%
	0.5	41.4±17.6	20.0-67.0	42.6%
B	2.0	33.0±3.5	27.0-38.0	10.7%
	1.0	26.0±2.4	21.0-30.0	9.3%
	0.5	15.5±3.4	8.0-21.0	22.0%
C	2.0	41.3±3.6	34.0-47.0	8.6%
	1.0	34.1±3.5	28.0-41.0	10.2%
	0.5	18.1±2.3	14.0-23.0	12.6%

Location	Depth (m)	Average value (×10^-4 m³/m³)	Range (×10^-4 m³/m³)	Variation coefficient
A1	2.0	38.1±1.8	35.0-40.0	4.8%
	1.0	27.7±1.4	26.0-30.0	5.1%
	0.5	17.0±1.6	15.0-19.0	9.3%
A2	2.0	64.3±3.6	59.0-70.0	5.6%
	1.0	39.4±8.1	23.0-51.0	20.4%
	0.5	17.1±5.1	11.0-26.0	29.3%
B	2.0	42.6±3.2	38.0-47.0	7.4%
	1.0	28.0±2.0	24.0-30.0	7.1%
	0.5	17.5±1.7	15.0-20.0	9.7%
C	2.0	37.1±2.0	35.0-40.0	5.7%
	1.0	28.6±0.7	28.0-30.0	2.8%
	0.5	12.1±1.0	11.0-14.0	8.8%

Position-Quarter	Depth (m)	Diffusion coefficient	Position-Quarter	Depth	Diffusion coefficient
Farmland (A1) -Spring	0.5	1.49±0.02	Farmland (B)-Summer	0.5 m	1.58±0.01
	1.0	1.46±0.02		1.0 m	1.56±0.01
	2.0	1.45±0.01		2.0 m	1.53±0.00
Grassland (A2) -Spring	0.5	1.49±0.03	Forest land (C)-Summer	0.5 m	1.57±0.00
	1.0	1.46±0.03		1.0 m	1.56±0.00
	2.0	1.45±0.02		2.0 m	1.53± 0.01
Farmland (B) -Spring	0.5	1.50±0.01	Farmland (A1)-Autumn	0.5 m	1.43±0.00
	1.0	1.47±0.01		1.0 m	1.46±0.00
	2.0	1.45±0.01		2.0 m	1.48±0.06
Forest land (C) -Spring	0.5	1.52±0.01	Grassland (A2)-Autumn	0.5 m	1.43±0.00
	1.0	1.49±0.00		1.0 m	1.44±0.01
	2.0	1.49±0.01		2.0 m	1.47±0.00
Farmland (A1) -Summer	0.5	1.55±0.00	Farmland (B)- Autumn	0.5 m	1.43±0.01
	1.0	1.55±0.01		1.0 m	1.44±0.00
	2.0	1.52±0.01		2.0 m	1.48±0.00
Grassland (A2) -Summer	0.5	1.56±0.01	Forest land (C)- Autumn	0.5 m	1.44±0.00
	1.0	1.55±0.00		1.0 m	1.47±0.01
	2.0	1.53±0.01		2.0 m	1.49±0.01

Spatio-temporal variation of soil CO₂concentration in Loess Area of northwestern Shanxi Province, China

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Position (Quarter)	Average moisture content				Average organic matter content (g/kg)
Position (Quarter)	0.0-0.5 m	0.6-1.0 m	1.1-2.0 m	0.0-2.0 m	0-2 m
A1 (Spring)	13.87%±0.38%	13.02%±0.44%	12.06%±0.53%	12.75%±0.89%	6.42±2.61
A2 (Spring)	10.47%±2.33%	14.04%±1.20%	13.63%±2.17%	12.95%±2.42%	7.54±4.78
B (Spring)	11.45%±1.07%	13.14%±0.47%	12.14%±0.51%	12.22%±0.89%	5.25±3.02
C (Spring)	10.59 %±0.90%	9.96%±0.31%	10.0%±2.00%	10.18%±1.43%	6.21±3.28
A1 (Summer)	7.47%±1.57%	6.53%±0.29%	7.75%±1.36%	7.38%±1.29%	6.59±2.41
A2 (Summer)	7.02%±2.47%	9.30%±0.83%	12.26%±2.17%	9.85%±2.93%	7.16±4.82
B (Summer)	6.47%±1.28%	6.57%±0.79%	7.08%±0.84%	6.80%±0.94%	5.55±3.02
C (Summer)	10.72%±4.87%	5.34%±0.26%	6.87%±0.38%	7.52%±3.20%	7.10±4.09
A1 (Autumn)	12.39%±1.11%	9.00%±0.02%	7.24%±0.01%	8.97%±2.45%	6.26±2.36
A2 (Autumn)	13.25%±1.23%	10.36%±0.01%	9.30%±0.01%	10.87%±1.91%	7.14±4.84
B (Autumn)	11.62%±0.48%	10.82%±0.01%	7.22%±0.01%	9.22%±2.20%	6.15±4.86
C (Autumn)	10.29%±1.81%	6.86%±0.01%	7.00%±0.02%	7.83%±2.10%	6.47±2.90