Showing papers by "Guohe Huang published in 2023"

Strategy to Enhance Geological CO ₂ Storage Capacity in Saline Aquifer

Abstract: Geological CO2 storage is an emerging topic in energy and environmental community, which is, as a commonly accepted sense, considered as the most promising and powerful approach to mitigate the global carbon emissions during the transition to net-zero. Of the geological media which initially considered cover the saline aquifers, oil and gas reservoirs, coal beds, and potentially basalts, up to now only the first two choices have been proven to be the most capable storage sites and successfully implemented at pilot/commercial scales. Here, two tandem papers propose novel strategies for the first time, by synthesizing and utilizing new high-dryness CO2 foam, to enhance geological CO2 storage capacity in saline aquifer and oil and gas reservoirs. In this paper, a new high-dryness CO2 foam is synthesized and injected into the saline aquifers to explore the storage capacity enhancement, with the unique foam-induced advantages of sweep area expansion and storage efficiency improvement. Such a new idea is specifically evaluated and validated through a series of static analytical and dynamic performance experiments. With the optimum surfactant concentration of 0.5 wt%, the foaming volume and quality are determined to be 521 mL and 80.81%, respectively, which also shows excellent salt tolerance with 45,000 ppm Na+, 25,000 ppm Ca2+, and 25,000 ppm Mg2+. Moreover, the water consumption for CO2 storage decreases from 464.31 g/mol at 25% foam quality to 67.38 g/mol at 85% foam quality by using the new CO2 foam. Overall, the newly synthesized CO2 foam could effectively enhance geological CO2 storage capacity and concurrently diminish water consumption, therefore realizing the win-win environment and economic benefits.

Water Self-Purification with Zero External Consumption by Livestock Manure Resource Utilization.

Abstract: Improper disposal of waste biomass and an increasing number of emerging contaminants (ECs) in water environment are universal threats to the global environment. Here, we creatively propose a sustainable strategy for the direct resource transformation of livestock manure (LM) into an innovative catalyst (Fe-CCM) for water self-purification with zero external consumption. ECs can be rapidly degraded in this self-purification system at ambient temperature and atmospheric pressure, without any external oxidants or energy input, accompanied by H2O and dissolved oxygen (DO) activation. The performance of the self-purification system is not affected by various types of salinity in the wastewater, and the corresponding second-order kinetic constant is improved 7 times. The enhanced water self-purification mechanism reveales that intermolecular forces between anions and pollutants reinforce electron exchange between pollutants and metal sites on the catalyst, further inducing the utilization of the intrinsic energy of contaminants, H2O, and DO through the interfacial reaction. This work provides new insights into the rapid removal of ECs in complicated water systems with zero external consumption and is expected to advance the resource utilization of livestock waste.

Litter, Root, and Mycorrhiza Input Affected Soil Microbial Community Structure in Schima superba Pure Forest in Subtropical China

Abstract: During forest vegetation rehabilitation, changes in aboveground litter and underground root inputs affect soil microbial communities. Clarifying the effects of forest ecosystem carbon inputs on soil microbial community structure can provide a theoretical basis for the microbial driving mechanism of soil fertility evolution and ecosystem rehabilitation of vegetation rehabilitation in degraded red soil. Our research focuses on a Schima superba pure forest recovered from eroded and degraded red soil in a subtropical region. Five treatments were set as follows: control treatment (CT), mycorrhiza (M), root + mycorrhiza (RM), litter + root + mycorrhiza (LRM), and double litter + root + mycorrhiza (DLRM). We used Illumina HiSeq technology to study the effects of different organic carbon inputs on soil microbial community structure. The results showed that all organic carbon input treatments reduced the total population of soil bacteria by 55–79%; M, RM, and DLRM treatments increased the quantity of operational taxonomic units (OTUs) by 25–37%, ACE index by 25–34%, and Chao1 index by 28–39%. Acidobacteria, Proteobacteria, and Actinobacteria were the dominant bacteriophyta in the Schima superba pure forest soil. The relative abundance of Alphaproteobacteria decreased by 55% under LRM treatment, and Thermoleophilia increased by 81% under M treatment. The dominant fungal phyla were Basidiomycota and Ascomycota. RM, LRM, and DLRM treatments reduced the relative abundance of Sordariomycetes by 46–64% and increased the relative abundance of Mortierellomycetes by 251–615%. The order of effects of different organic carbon inputs on the bacterial community composition at the phylum level was LRM ˃ RM ˃ M ˃ DLRM and that on the fungal community composition was DLRM ˃ LRM and RM ˃ M. Alphaproteobacteria, Thermoleophilia, Sordariomycetes, and Mortierellomycetes were the main microbial groups affected by changes in organic carbon inputs. Soil organic carbon and total nitrogen were the key factors affecting the change of Mortierellomycetes. The bacterial community mainly affected the activity of soil acid invertase, while the fungal community affected the activities of various enzymes, with positive or negative effects. We concluded that the organic carbon inputs changed the species and quantity of soil microorganisms in the Schima superba forest, and the influence of organic carbon input on the fungal community structure was greater than that of bacteria.

A Stepwise Regression and Statistical Downscaling Approach for Projecting Temperature Variations under Multiple RCP Scenarios

Abstract: With the rapid development of Central China, the temperature in this region is continuously increasing. Extreme weather events (e.g., high-temperature weather for many consecutive days) are becoming frequent. In order to provide future theoretical guidance on the direction of local development and the prevention of extreme natural disasters, the daily datasets of 12 meteorological stations in three provinces were collected. The corresponding predictors from 25 large-scale climatic factors were then screened using stepwise regression. A stepwise regression and statistical downscaling (SRSD) approach was developed to establish the statistical relationship. The future temperature results were projected by the weather generator, and the probability of extreme weather occurrence was analyzed by extreme values. The results indicate that future temperature in Central China shows an increasing trend from 2036 to 2065 and 2066 to 2095, with the representative concentration pathway 4.5 (RCP4.5) scenario showing a greater increase in temperature than the representative concentration pathway 8.5 (RCP8.5) scenario. Hunan Province has the largest temperature increase, followed by Hubei Province and Henan Province. The average annual duration of heat waves in Central China is 74.7 days.

Factorial CGE‐Based Analysis for the Indirect Benefits of the Three Gorges Project

Abstract: Large‐scale hydraulic projects (LHPs) have become increasingly significant in river basin flood‐risk management. Although LHPs’ direct flood‐retention benefits have been clearly shown, there has been a dearth of a comprehensive examination of their indirect implications, which can be more long‐lasting and substantial in both environmental and economic terms. Thus, this study develops a factorial computable general equilibrium (CGE)‐based LHP‐effect analysis approach (FLEA) to quantify the indirect impacts of LHPs and simulate postflood recovery strategies under diverse scenarios. The FLEA integrates a factorial analysis with a dynamic CGE framework, including a flood module that connects hydraulic initiatives to the economy during floods. The FLEA is applied to the Three Gorges Project (TGP). The results demonstrate that ∼$57 billion in Gross Domestic Product (GDP) and ∼12.9 Mt CO2eq reduction would be created annually through supply chains by the TGP. When floods strike, the TGP has the potential to save ∼$21 billion in GDP directly and reduce long‐term GDP losses by ∼50% throughout the reconstruction period. The TGP can have a considerable indirect impact on manufacturing. Furthermore, improved regulations and maintenance for the TGP may be desired for mitigating long‐term flood‐related losses, which is more crucial than aggressive postflood fiscal stimuli.

Correction to "Water Self-Purification with Zero-External Consumption by Livestock Manure Resource Utilization".

Abstract: ADVERTISEMENT RETURN TO ISSUEPREVAddition/CorrectionNEXTORIGINAL ARTICLEThis notice is a correctionCorrection to “Water Self-Purification with Zero-External Consumption by Livestock Manure Resource Utilization”Wenrui CaoWenrui CaoMore by Wenrui Cao, Zhongkai WangZhongkai WangMore by Zhongkai Wang, Peng ZhangPeng ZhangMore by Peng Zhang, Yingtao SunYingtao SunMore by Yingtao Sun, Zhiju XieZhiju XieMore by Zhiju Xie, Chun HuChun HuMore by Chun Hu, Shuguang WangShuguang WangMore by Shuguang Wanghttps://orcid.org/0000-0002-9381-1771, Guohe HuangGuohe HuangMore by Guohe Huang, and Lai Lyu*Lai LyuMore by Lai Lyuhttps://orcid.org/0000-0002-5624-961XCite this: Environ. Sci. Technol. 2023, 57, 13, 5499Publication Date (Web):March 23, 2023Publication History Received2 March 2023Published online23 March 2023Published inissue 4 April 2023https://doi.org/10.1021/acs.est.3c01673Copyright © 2023 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views359Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (1024 KB) Get e-AlertsSupporting Info (1)»Supporting Information Supporting Information Get e-Alerts

Copula function with Variational Bayesian Monte Carlo for unveiling uncertainty impacts on meteorological and agricultural drought propagation

Abstract: Agricultural drought (AD) is disastrous to natural and socioeconomic systems, and the propagation of meteorological drought (MD) plays an essential role in the occurrence of AD. However, how uncertainty affects the mechanism of propagation from MD to AD remains unclear. In this study, a novel method called C-VBMC is developed through coupling copula function with Variational Bayesian Monte Carlo (VBMC). The developed C-VBMC is then applied to the Aral Sea Basin to demonstrate its feasibility and capability. Results indicate that the method could effectively quantify the drought propagation probability under the impact of uncertainty. Several findings can be summarized: (1) compared with the low elevation areas, the propagation time and relationship between MD and AD tend to be longer and weaker in spring and winter at mid-high elevation areas; (2) drought propagation characteristics are significantly affected by seasonality, altitude, potential evapotranspiration, precipitation and soil moisture; (3) the posterior distribution of copula parameter by VBMC is similar with Markov chain Monte Carlo (MCMC), and VBMC only takes about 50% and 5% of the computation time required by MCMC for univariate and bivariate copula functions, the results highlight the superiority and flexibility of VBMC for large datasets; (4) the probability of AD occurrence and the uncertainty range are easily affected by same and more severe level MD; (5) the propagation probabilities tend to be underestimated without uncertainty impact, and the uncertainty range is lower than 0.05 for most grids. This study is helpful for drought warning management and disaster prevention systems.

Electronic Structure Modulation of Bimetallic Sulfides for Efficient Sacrificial-Agent-Free Photocatalytic H2 Evolution

Abstract: The consumption of sacrificial agents is inevitable to improve the separation and utilization of electron–hole pairs in photocatalytic H2 evolution, which is contrary to the current vision of carbon neutrality and carbon peak. Here, bimetallic sulfides composed of highly dispersed Cu-doped ZnS composites were proposed, exhibiting an optimal H2 evolution activity of over 1569 μmol/g at 2 h (0.5 g/L catalyst) under visible light irradiation at pH = 3 with zero sacrificial agents or cocatalyst consumption, which is approximately 21 times higher than that of pure ZnS. A series of advanced characterizations indicate that the Cu atoms have been doped into the ZnS lattices, exposing a CuS (101) facet on the surface of the ZnS (111) facet. This results in a narrower energy bandgap (Eg = 2.6 eV) in optimal bimetallic sulfides (ZCS0.1), which is beneficial for absorbing more visible light. In particular, the introduction of Cu induces a nonequilibrium charge distribution on the ZCS0.1 surface, thereby boosting the separation and migration of photoinduced carriers. According to theory calculation (DFT) results, the hydrogen adsorption free energy (ΔGH) of ZCS0.1 is reduced than that of pure ZnS, facilitating the efficient reduction of H+/H2O around the electron accumulation regions and oxidation of H2O around the photogenerated hole (h+) regions. The modulation of the surface electronic structure is significant for effectively separating and utilizing photoinduced carriers under natural conditions without the consumption of sacrificial agents.

Macroscale altimetry-based estimation and analyses of wave power: A foundation of wave energy development over Canada

Abstract: Wave power is essential to carbon neutrality and other energy strategies. Its estimation and analyses at macroscales are enabled by extensive satellite altimetric data, but several challenges or questions exist. Thus, this study develops an advanced macroscale altimetry-based wave-power estimation and analysis (WPEA) method through integrating regionalized ensemble estimates of wave heights, wind speeds and wave periods, models of wave energy flux, indices of flux variabilities and wave power potentials, and statistical analyses of associations between wave power and selected externalities (e.g., offshore distances, water depths, ice-free days, and wind speeds). The method is applied to all Canadian waters, which reveals a series of findings. For instance, Pacific Ocean, Atlantic Ocean, St. Lawrence, and Davis Strait in Canada are suitable for harvesting wave energy, because of considerable fluxes and low variabilities of wave energy at various timescales. Annual total wave power (approximately 2.04 PWh) largely exceeds national electricity consumption (249 TWh in 2021). The regionalized ensemble estimation helps WPEA enhance wave-power estimation accuracy under significant effects of data uncertainty. At the national scale, high wave power tends to be produced over remote, deep, windy, eastern waters and, without the consideration of technological applicability, over ice-free, southern waters. Potential associations of wave power with the externalities present seasonalities and heterogeneities under intensification effects of power-externality covariations and tech-applicability restrictions. Besides advancing wave-power estimation, analyses and modeling at macroscales (including the globe), this study provides data and scientific supports for studies and practices of local, regional and national wave energy development over Canada.