Pattern of microbial community composition and functional gene repertoire associated with methane emission from Zoige wetlands, China-A review

Innovating Taiwan's greenhouse gas estimation: A case study of atmospheric methane using GeoAI-Based ensemble mixed spatial prediction model

This study addresses a gap in atmospheric greenhouse gas research, focusing on methane (CH4), a gas with a global warming potential 80 times greater than carbon dioxide (CO2). Unlike prior studies that focus on emission sources and reduction strategies, this research emphasizes the spatiotemporal variations in atmospheric CH4 concentrations, providing new perspectives on global climate mitigation efforts. A novel GeoAI-based ensemble mixed spatial prediction model was developed, integrating multiple machine learning algorithms and considering various factors to accurately estimate CH4 concentrations across Taiwan. In the context of global net-zero emissions, this study offers a robust approach to assess spatial variations in CH4 concentrations, providing valuable insights into the effectiveness of greenhouse gas reduction policies and climate strategies. Key factors influencing CH4 levels include aquaculture, livestock, transportation land use, wind speed, national CH4 emissions, net greenhouse gas emissions, population density, quarry sites, solar radiation, seasonal variations, residential areas, temples, CO2 removal levels, and primary pollutants (e.g., NO2, NOx, PM2.5, PM10, CO, CO2, SO2, and O3). Seasonal analysis revealed higher CH4 concentrations in spring and winter, and lower levels in summer and autumn. The model demonstrated high explanatory power with R2 values of 0.99, 0.82, 0.98, and 0.67 across training, testing, cross-validation, and external validation datasets. This study presents a model that enhances the understanding of the dynamic factors influencing methane concentration variations. The methodology developed in this research can serve as a reference for other regions and timeframes, potentially offering key insights for the formulation of effective global climate mitigation strategies.

Resilient green infrastructure: Navigating environmental resistance for sustainable development, social mobility in climate change policy

This study explores the complex dynamics of environmental resistance, policy stability, skill development, and green initiatives in light of the growing worldwide concerns about climate change. COP27 and the G20 Summit show that as microcosm of the global discourse, provides a unique opportunity to study it. This research sought to thoroughly investigate, the links among green infrastructure, green technological innovation, policy stability, skill development, and their combined effects on social mobility and climate change (Case-1), it also discusses the global talk on climate change in COP27 and G20 (Case-2). In Case-1 data were analyzed through the use of structural equation modeling (SEM) by adopting a quantitative approach, and in Case-2 data were analyzed using theme analysis by applying a qualitative approach. Using a mixed-method research approach, the study surveyed 375 locals living close to the CPEC corridor quantitatively and interviewed ten important stakeholders, including elected officials, environmental activists, and community leaders, qualitatively. The survey highlighted the complex perspectives and experiences of citizens with green programs and environmental legislation in the CPEC zone. The study revealed the perceptions and experiences of residents regarding green initiatives and environmental policies within the CPEC region. Key stakeholders provided valuable insights into policy formulation and ongoing environmental sustainability efforts. The analysis unveiled intricate relationships between green infrastructure, technological innovation, policy stability, skill development, and their collective impact on climate change and social mobility. Notably, the study identified a critical research gap in understanding these dynamics within regions undergoing substantial economic development. Policy formulation and continuing environmental sustainability efforts were aided by key stakeholders' ideas. Green infrastructure, technological innovation, policy stability, skill development, and their overall influence on climate change and social mobility were all examined. Notably, the study found a critical research vacuum in understanding these processes inside rapidly developing economies. Policymakers, environmental groups, and communities managing the fine line between economic success and environmental responsibility will find great value in the findings. This study is unique because it examines issues on climate change from a local perspective in a region that is rapidly developing economically, it also adds value to the climate change challenges on the global level. This study presents a substantial theoretical contribution by examining the intricate interactions among environmental opposition, policy stability, skill development, and green initiatives within the CPEC against the backdrop of global climate change concerns.

CH4 control and nitrogen removal from constructed wetlands by plant combination

Global warming trend is accelerating. This study proposes a green and economical methane (CH4) control strategy by plant combination in constructed wetlands (CWs). In this study, a single planting of Acorus calamus L. hybrid constructed wetland (HCW-A) and a mixed planting of Acorus calamus L. and Eichhornia crassipes (Mart.) Solms hybrid constructed wetland (HCW-EA) were constructed. The differences in nitrogen removal performance and CH4 emissions between HCW-A and HCW-EA were compared and analyzed. The findings indicated that HCW-EA demonstrated significant improvements over HCW-A, with NH4+-N and TN removal rates increasing by 21.61% and 16.38% respectively, and CH4 emissions decreased by 43.36%. The microbiological analysis results showed that plant combination promoted the enrichment of Proteobacteria, Alphaproteobacteria and Bacillus. More nitrifying bacteria carrying nxrA genes and denitrifying bacteria carrying nirK genes accelerated the nitrogen transformation process. In addition, the absolute abundance ratio of pmoA/mcrA increased, reducing the release of CH4.

Patterns of bacterial communities in the rhizosphere and rhizoplane of alpine wet meadows

Wet meadows, a type of wetland, are vulnerable to climate change and human activity, impacting soil properties and microorganisms that are crucial to the ecosystem processes of wet meadows. To decipher the ecological mechanisms and processes involved in wet meadows, it is necessary to examine the bacterial communities associated with plant roots. To gain valuable insight into the microbial dynamics of alpine wet meadows, we used Illumina MiSeq sequencing to investigate how environmental factors shape the bacterial communities thriving in the rhizosphere and rhizoplane of three plant species: Cremanthodium ellisii, Caltha scaposa, and Cremanthodium lineare. The most abundant bacterial phyla in rhizosphere and rhizoplane were Proteobacteria > Firmicutes > Actinobacteria, while Macrococcus, Lactococcus, and Exiguobacterium were the most abundant bacterial genera between rhizosphere and rhizoplane. The mantel test, network, and structure equation models revealed that bacterial communities of rhizosphere were shaped by total nitrogen (TN), soil water content (SWC), soil organic carbon (SOC), microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), pH, however, rhizoplane bacterial communities exhibited varying results. The bacterial communities exhibited significant heterogeneity, with stochastic process predominating in both the rhizosphere and rhizoplane. PICRUSt2 and FAPROTAX analysis revealed substantial differences in key biogeochemical cycles and metabolic functional predictions. It was concluded that root compartments significantly influenced the bacterial communities, although plant species and elevation asserted varying effects. This study portrays how physicochemical properties, plant species, and elevations can shift the overall structure and functional repertoire of bacterial communities in alpine wet meadows.

Fatty acid metabolization and insulin regulation prevent liver injury from lipid accumulation in Himalayan marmots

Fat storage and weight gain are dominant traits for hibernating mammals. However, excessive fat accumulation may cause liver damage. Here, we explore the lipid accumulation and metabolic processes of the Himalayan marmot (Marmota himalayana), a hibernating rodent species. We find that the unsaturated fatty acid (UFA) content in food was consistent with a large increase in the body mass of Himalayan marmots. Metagenomic analysis shows that Firmicutes Bacterium CAG:110 plays a synergistic role by synthesizing UFAs, which is demonstrated by fecal transplantation experiments, indicating that the gut microbiome promotes fat storage in Himalayan marmots for hibernation. Microscopic examination results indicate that the risk of fatty liver appears at maximum weight; however, liver function is not affected. Upregulations of UFA catabolism and insulin-like growth factor binding protein genes provide an entry point for avoiding liver injury.

Bioengineered biochar as smart candidate for resource recovery toward circular bio-economy: a review

Biochar's ability to mediate and facilitate microbial contamination degradation, as well as its carbon-sequestration potential, has sparked interest in recent years. The scope, possible advantages (economic and environmental), and future views are all evaluated in this review. We go over the many designed processes that are taking place and show why it is critical to look into biochar production for resource recovery and the role of bioengineered biochar in waste recycling. We concentrate on current breakthroughs in the fields of engineered biochar application techniques to systematically and sustainable technology. As a result, this paper describes the use of biomass for biochar production using various methods, as well as its use as an effective inclusion material to increase performance. The impact of biochar amendments on microbial colonisation, direct interspecies electron transfer, organic load minimization, and buffering maintenance is explored in detail. The majority of organic and inorganic (heavy metals) contaminants in the environment today are caused by human activities, such as mining and the use of chemical fertilizers and pesticides, which can be treated sustainably by using engineered biochar to promote the establishment of a sustainable engineered process by inducing the circular bioeconomy.

Evaluation of comprehensive monthly-gridded methane emissions from natural and anthropogenic sources in China

The observed atmospheric methane (CH₄) concentration in China has grown rapidly in recent years, showing marked spatial-temporal variation. However, existing inventories, most of which are yearly, provincial, and incomplete, have failed to reflect the spatial variation and seasonal trends of CH₄ emissions. This study aims to develop a high-resolution (0.05° × 0.05°) monthly inventory of CH₄ emissions across China in 2015 from eight major natural and anthropogenic sources. The inventory evaluation of CH₄ emissions was based on the gridded activity data and high spatial-temporal resolution emission factors, which were estimated by their relationship with environmental factors in most source sectors. The results showed that the annual CH₄ emissions across China were 61.65 Tg, of which 85% was associated with anthropogenic emissions. Energy activities, livestock, and paddy fields were the largest contributors, accounting for 31% (19.06 Tg), 24% (15.01 Tg) and 19% (11.45 Tg) of the total emissions respectively, followed by vegetation (7%, 4.52 Tg), wetlands (7%, 4.20 Tg), wastewater (6%, 3.43 Tg), municipal solid waste, (4%, 2.59 Tg) and biomass burning (2%, 1.40 Tg). However, these proportions varied by month; paddy fields, vegetation, and wetlands emitted the most CH₄ in July and August with approximately 29%, 14%, and 8% of total emissions, respectively, and least in January and December with 0%, 2%, and 2%, respectively, leading to a CH₄ emissions peak in summer and a valley in winter. Moreover, the major contributing provinces of CH₄ emissions in China were Inner Mongolia, Shanxi, Sichuan, Guizhou, and Hunan, accounting for 33% of China's total emissions. The dominant emission sources were energy activities in Mongolia, Shanxi, and Guizhou; livestock in Sichuan; and paddy fields in Hunan. This improved inventory of CH₄ emissions can help understanding the spatial-temporal variation of CH₄ concentration in the atmosphere and formulating regional-seasonal-specific emission reduction policies.

Greenhouse gas emissions from constructed wetlands are mitigated by biochar substrates and distinctly affected by tidal flow and intermittent aeration modes

Biochar substrates and tidal flow (TF) and intermittent aeration (IA) operation modes have recently been applied to improve the treatment performance of constructed wetlands (CWs), but their roles in regulating greenhouse gas (GHG) emissions from CWs are still unclear. In this preliminary study, CO₂, CH₄ and N₂O fluxes and associated microbial characteristics in four groups of subsurface-flow CWs, i.e., ceramsite CWs (C-CWs), biochar-amended CWs (B-CWs), intermittently aerated B-CWs (AB-CWs) and tide-flow B-CWs (TB-CWs), were comparatively investigated. The results showed that biochar amendment significantly mitigated CH₄ and N₂O fluxes from the CWs by supporting higher abundances of mcrA and nosZ genes and higher ratios of pmoA/mcrA and nosZ/(nirK + nirS), thus reducing global warming potential (GWP, a decrease of 55.8%), in addition to promoting total nitrogen (TN) removal by 41.3%, mainly by increasing the abundances and activities of nitrifiers and denitrifiers. The TF mode efficiently improved nitrogen removal, but it greatly increased GHG fluxes since large amounts of GHGs escaped from the empty CW matrix after water draining. IA abated GHG emissions from the CWs, mainly after aeration. TF and IA decreased the abundances of functional bacteria and archaea related to C and N transformation, except nitrifiers, and shaped the microbial community structures. The application of a biochar substrate and IA mode can facilitate the design and operation of CWs in a more ecologically sustainable way.