Shihao Cui’s research while affiliated with Aarhus University and other places

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Publications (6)


Greenhouse gas emissions and global warming potential across treatments under different temperatures
a Cumulative CO2 emissions of different treatments at 10 °C. b Cumulative CO2 emissions of different treatments at 20 °C. c Cumulative CH4 emissions of different treatments at 10 °C. d Cumulative CH4 emissions of different treatments at 20 °C. e CO2 equivalents of different treatments at 10 °C. f CO2 equivalents of different treatments at 20 °C. g Total global warming potential (GWP) of different treatments at 10 °C. h Total global warming potential (GWP) of different treatments at 20 °C. Treatments are distinguished by both color and symbol shape across panels. In panels a-d, treatments are represented by green triangles/circles (DOS), blue triangles/circles (ROS), and red triangles/circles (ROSB). In panels e-f, stacked bars show contributions from CO2 (purple) and CH4 (light green) to total CO2-equivalent emissions for each treatment. In panels g-h, total GWP is shown using blue bars (10 °C) and red bars (20 °C), with a dashed line linking the mean values across treatments to highlight treatment-level differences. Data are presented as means ± standard error (n = 3).
Fourier transform infrared spectra analysis of burnt and unburnt topsoil
a Fourier transform infrared spectra of burnt and unburnt topsoil (0 – 1 cm depth). Shaded areas highlight major absorption regions associated with key functional groups, including cellulose, aliphatics, aromatics, phenolics, and polysaccharides. b Stability indices of burnt and unburnt topsoil. Bars represent means ± standard error (n = 3). Green and purple lines or bars represent unburnt and burnt soil, respectively, across both panels.
Microbial community composition in different treatments after incubation
a Venn diagram of bacterial OTUs at 10 °C. b Venn diagram of bacterial OTUs at 20 °C. c Venn diagram of archaeal OTUs at 10 °C. d Venn diagram of archaeal OTUs at 20 °C. e Relative abundances of the top 10 bacterial families. f Relative abundances of the top 10 archaeal families. In panels a-d, different treatments are indicated by different colors: at 10 °C, treatments are represented by lavender (DOS10), sky blue (ROS10), and teal grey (ROSB10); at 20 °C, treatments are shown in olive green (DOS20), slate blue (ROS20), and dusty rose (ROSB20).
Predicted enrichment of microbial metabolic pathways under different treatments
a Predicted metabolic pathway enrichment in different treatments at 10 °C. b Predicted metabolic pathway enrichment in different treatments at 20 °C. Functional predictions were generated using PICRUSt from 16S rRNA gene sequencing data and mapped to KEGG Level 3 metabolic categories. Z-scores represent the relative enrichment of various metabolic pathways across different treatments. Pathways are grouped by functional categories, such as amino acid metabolism, carbohydrate metabolism, other amino acid metabolism, lipid metabolism, and energy metabolism. Global and overview maps refer to broad, overarching pathways that provide a high-level summary of major biological processes, integrating various metabolic and cellular functions. Colored dots represent different treatments, with lighter colors used for 10 °C and darker shades for 20 °C. Specifically, green indicates DOS, blue indicates ROS, and red indicates ROSB. Dot position reflects the Z-score for each pathway under each treatment, illustrating shifts in microbial metabolic potential.
CH4 cycling pathways and associated gene abundances in different treatments
a KEGG methanogenesis pathways, including hydrogenotrophic methanogenesis and acetoclastic methanogenesis. b KEGG methanotrophy pathways, including anaerobic CH4 oxidation and aerobic CH4 oxidation. c Abundance of CH4 cycle-related enzymes. d Abundance of methanogenesis (mcrA) and main methanotrophy genes (pmoA and ANME-3). In panels a, b, enzyme names are color-coded according to functional groups and match the colors used in panel c. In panel d, data are presented as means ± standard error (n = 3). Abbreviations are explained in Supplementary Table 3.

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Controlled burning of peat before rewetting modifies soil chemistry and microbial dynamics to reduce short-term methane emissions
  • Article
  • Full-text available

May 2025

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43 Reads

Shihao Cui

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Haonan Guo

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[...]

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Shubiao Wu

Increased CH4 emissions from rewetted organic soils can undermine the climate benefits of reduced CO2 release. This is especially problematic in low-lying areas that tend to remain waterlogged and act as potential CH4 hotspots. Here we test whether burning the soil surface before rewetting can reduce CH4 emissions. Using laboratory experiments with soil cores collected from degraded farmland in Denmark, we found that rewetting organic soils following burning reduced CH4 emissions by more than 95% over a 90-day period compared to rewetting alone. The reduction was likely associated with changed soil chemistry such as increased soil carbon stability and the decrease in methanogen abundance and activity. Our results suggest that targeted burning could help suppress short-term CH4 emissions after rewetting. However, long-term field studies are needed to understand whether this effect persists and to assess potential ecological risks such as pollution runoff, before any broader field-scale implementation is considered.

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Figure 4. Greenhouse gas emissions and reductions in CO 2 equivalents. (a) Total greenhouse gas emissions illustrating the overall climate impact. (b) Greenhouse gas reductions in rewetted treatments (0 and 8 cm) compared to drained treatments (−8 cm). Error bars represent means ± 95% confidence interval (n = 9 for total emissions; n = 3 for reductions). Statistically significant differences between land-use types and water-level treatments, analyzed using linear mixed-effect models, are denoted as follows: *P < 0.05, **P < 0.01, and ****P < 0.0001.
Harnessing the Low-Hanging Fruits: Rewetting Unmanaged Marginal Organic Soils to Achieve Maximal Greenhouse Gas Reduction

March 2025

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32 Reads

Environmental Science and Technology

Rewetting drained peatlands is a promising strategy for mitigating carbon dioxide (CO2) emissions, transforming these areas from carbon sources to sinks. Despite the well-known climate benefits, practical implementation is often hampered by conflicts between environmental goals and farmers’ economic interests. Identifying optimal rewetting locations that maximize greenhouse gas (GHG) reduction while minimizing agricultural disruption is crucial to advancing this process. However, there is currently limited scientific evidence to guide these decisions. To identify “low-hanging fruits”, 12 sites were selected for 4-month incubations to investigate the effects of four land uses (grass-cut, grass-graze, arable, and unmanaged) on CO2 and methane (CH4) emissions postrewetting. Results showed that unmanaged sites exhibited the highest potential for GHG reduction (2015 mg CO2-eq m–2 day–1, 89.9%), followed by grass-graze, grass-cut, and arable sites, reflecting a gradient of management intensity. These insights suggest that prioritizing rewetting of unmanaged areas while delaying interventions on arable lands could yield greater climate benefits and enhance farmers’ acceptance. Additionally, emission variability across sites was linked to soil properties, indicating that soils with a higher organic carbon content (for greater CO2 reduction) and lower bacterial diversity (for reduced CH4 production) offer the greatest GHG reduction potential. This study provides crucial scientific evidence to guide targeted peatland rewetting efforts, supporting net-zero emission goals.




Figure 1. (a) Locations and wetland types of the 22 EC sites across different Kö ppen climate zones. (b) Annual-average meteorological and water table conditions of different types of wetlands. The values for each site were calculated by averaging daily measurements over one or more complete years. The white central marks, white dots, and the bottom and top end points of diamond boxes indicate the median, average, and the 25th and 75th percentiles, respectively. The whiskers extend up and down to the data points with maximum and minimum values. Outliers exceeding 1.5 times the interquartile range are labeled. SW-IN, incoming shortwave radiation; NETRAD, net radiation; TA, air temperature; P, precipitation; WTD, water table depth; WS, wind speed.
Figure 2. (a) SEM model built based on the interactions between environmental drivers and methane fluxes. The red arrows indicate the direct effect of environmental drivers on methane flux, and the blue arrows indicate the interactions among environmental drivers. (b) Schematic diagram showing the purposes of SEM and RDA analyses. (c) Schematic diagram showing the differences between various RF modeling strategies and their respective purposes. TA, air temperature; WTD, water table depth; TS, soil temperature; GPP, gross primary productivity; LE, latent heat turbulent flux; RECO, ecosystem respiration; FCH 4 , methane turbulent flux; SW-IN, incoming shortwave radiation; NETRAD, net radiation; P, precipitation; WS, wind speed.
Figure 3. (a) Heatmap showing the standardized direct, indirect, and total effects of environmental drivers on methane fluxes across 22 EC sites. Specific values are provided in Table S3. (b) Statistical analysis of the standardized effects (n = 22). Error bars represent mean ±95% confidence interval of standardized effects. Different capital letters indicate significant differences (P < 0.05) among environmental drivers under the same type of effect. Different lowercase letters indicate significant differences (P < 0.05) among the direct, indirect, and total effects of the same environmental driver. (c) Proportional distribution (%) of the indirect effect of air temperature on methane fluxes in different pathways across 22 EC sites (Materials and Methods). Specific values are provided in Table S4. (d) Statistical analysis of the portioned effects (n = 22). Error bars represent mean ±95% confidence interval of portioned effects. Different lowercase letters indicate significant differences (P < 0.05) among pathways. TA, air temperature; WTD, water table depth; TS, soil temperature; GPP, gross primary productivity; LE, latent heat turbulent flux; RECO, ecosystem respiration.
Unraveling Spatially Diverse and Interactive Regulatory Mechanisms of Wetland Methane Fluxes to Improve Emission Estimation

August 2024

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47 Reads

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2 Citations

Environmental Science and Technology

Methane fluxes (FCH4) vary significantly across wetland ecosystems due to complex mechanisms, challenging accurate estimations. The interactions among environmental drivers, while crucial in regulating FCH4, have not been well understood. Here, the interactive effects of six environmental drivers on FCH4 were first analyzed using 396,322 half-hourly measurements from 22 sites across various wetland types and climate zones. Results reveal that soil temperature, latent heat turbulent flux, and ecosystem respiration primarily exerted direct effects on FCH4, while air temperature and gross primary productivity mainly exerted indirect effects by interacting with other drivers. Significant spatial variability in FCH4 regulatory mechanisms was highlighted, with different drivers demonstrated varying direct, indirect, and total effects among sites. This spatial variability was then linked to site-specific annual-average air temperature (17.7%) and water table (9.0%) conditions, allowing the categorization of CH4 sources into four groups with identified critical drivers. An improved estimation approach using a random forest model with three critical drivers was consequently proposed, offering accurate FCH4 predictions with fewer input requirements. By explicitly accounting for environmental interactions and interpreting spatial variability, this study enhances our understanding of the mechanisms regulating CH4 emissions, contributing to more efficient modeling and estimation of wetland FCH4.


Fig. 1. Timeline of relevant research on the redox activity of geobatteries in the field of environmental science. Geobattery milestone: redox-active substances in aquatic systems proposed in 2021 with a red background [8]. Time points of natural organic matter (NOM) in 2007 [34], 2010 [99], 2014 [35], and 2019 [58] with orange backgrounds. Time points of pyrogenic carbon (PyC) in 2014 [36], 2016 [37], and 2018 [14] with dark green backgrounds. Time points of mixed-valent mineral phases (MMPs) in 2015 [38,39] with a blue background. Time points of microplastics in 2021 [173] and 2023 [22] with light green backgrounds.
Fig. 2. The potential reversible redox reaction in natural organic matter (NOM).
Fig. 5. Characterization techniques for redox activity of geobatteries. FTIR: Fourier transform infrared spectroscopy; NMR: Nuclear magnetic resonance; NEXAFS: Synchrotron-based near-edge X-ray absorption fine structure.
Application of geobatteries in anaerobic digestion.
Geobatteries in Environmental Biogeochemistry: Electron Transfer and Utilization

July 2024

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72 Reads

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8 Citations

Environmental Science and Ecotechnology

The efficiency of direct electron flow from electron donors to electron acceptors in redox reactions is significantly influenced by the spatial separation of these components. Geobatteries, a class of redox-active substances naturally present in soil–water systems, act as electron reservoirs, reversibly donating, storing, and accepting electrons. This capability allows the temporal and spatial decoupling of redox half-reactions, providing a flexible electron transfer mechanism. In this review, we systematically examine the critical role of geobatteries in influencing electron transfer and utilization in environmental biogeochemical processes. Typical redox-active centers within geobatteries, such as quinone-like moieties, nitrogen- and sulfur-containing groups, and variable-valent metals, possess the potential to repeatedly charge and discharge. Various characterization techniques, ranging from qualitative methods like elemental analysis, imaging, and spectroscopy, to quantitative techniques such as chemical, spectroscopic, and electrochemical methods, have been developed to evaluate this reversible electron transfer capacity. Additionally, current research on the ecological and environmental significance of geobatteries extends beyond natural soil–water systems (e.g., soil carbon cycle) to engineered systems such as water treatment (e.g., nitrogen removal) and waste management (e.g., anaerobic digestion). Despite these advancements, challenges such as the complexity of environmental systems, difficulties in accurately quantifying electron exchange capacity, and scaling-up issues must be addressed to fully unlock their potential. This review underscores both the promise and challenges associated with geobatteries in responding to environmental issues, such as climate change and pollutant transformation.

Citations (2)


... These ecosystems exhibit complex, nonlinear responses to climate anomalies, making them difficult to model. Cui et al. (2024) show that methane emissions from tropical wetlands are highly sensitive to microbial shifts caused by hydrological variation. Yet, the inclusion of these emissions in national reporting is uneven at best. ...

Reference:

Role of Informal Governance in Addressing Climate Change: A Comprehensive Review of Local and Community-Driven Solutions
Wetland hydrological dynamics and methane emissions

... A variety of trace elements were detected in the abyssal sediment (Table 1), which were closely associated with the co-present minerals. Clay minerals of muscovite can adsorb trace elements through ion exchange [35][36][37], while Fe-Mn (hydr)oxides also play a role in scavenging trace elements [38,39]. Active Fe-redox regions in deep-sea sediment can accumulate various trace elements, which may serve as active centers for coenzymes and catalyze methane production and nitrogen fixation [40][41][42]. ...

Geobatteries in Environmental Biogeochemistry: Electron Transfer and Utilization

Environmental Science and Ecotechnology