Including advanced thermochemical technologies in comparative life cycle assessment (LCA) of municipal organic waste management systems: A systematic review.

Microbial community divergence and environmental responses across multi-phase landfill environments.

Reactive oxygen species-mediated conversion of organic matter into humus: A meta-analysis on mechanisms and environmental implications.

Aluminum (Al) and iron (Fe) (hydr)oxides have been considered the primary phosphorus (P) sinks in many acidic soils. However, low contents of Al/Fe (hydr)oxides and their limited pH-dependent sorption capacity in temperate soils with pH 5.5-7 question their dominant role in P retention and suggest the importance of other P retention pathways. This study presents a newly developed nanoscale secondary ion mass spectrometry (NanoSIMS) method that spatially and operationally identifies inorganic phosphorus (IP) and organic phosphorus (OP) in natural soils by integrating 31 P 16 O 2 - /( 31 P - + 31 P 16 O 2 - ) and 12 C 14 N - /( 12 C - + 12 C 14 N - ) ratios. This method enables mapping IP and OP distributions on natural soil microaggregate surfaces. Our results exhibit that phyllosilicates and their associated OM spatially associated with over 85% of total P observed on microaggregate surfaces in four loamy, slightly acidic temperate soils in Southeast Germany. The association of phyllosilicates with OM doubles the P retention density (the proportion of surface area occupied by P within each mineral/OM constituent), highlighting the important role of phyllosilicate-OM associations in P retention beyond the individual P retention capacity of OM-free phyllosilicates. Spatial mapping revealed two contrasting P associations: (i) IP and myo -inositol hexaphosphate predominant on phyllosilicate surfaces with minimal N signals, and (ii) OP predominates in phyllosilicate-associated OM in the form of N-rich microbial biomass/necromass and plant residues. These distinct spatial patterns may imply potentially different microscale P associations, although their functional significance for soil P cycling requires further investigation with complementary spectroscopic methods. Our study demonstrates the spatial importance of phyllosilicates and phyllosilicate-associated OM for P retention through two distinct P association patterns in slightly acidic temperate soils with low Al/Fe (hydr)oxide contents. Establishing the functionality of these spatial patterns in controlling soil P availability requires further research integrating molecular speciation, desorption kinetics, and mineralization monitoring. • NanoSIMS spatially identifies organic (OP) and inorganic phosphorus (IP) patterns • Phyllosilicates associate >85% of total phosphorus (P) on microaggregate surfaces • Phyllosilicates associated with organic matter (OM) double P retention density • OP is primarily concentrated in nitrogen-rich OM • P retention dominates by phyllosilicate–OM associations in pH 5.5-7 temperate soils

Spatial distribution and environmental controls of n-alkanes in gulf of oman sediments: Implications for organic matter sources and cycling in subtropical active marginal seas.

Dissolved organic matter treatability and disinfection byproducts formation potential: Role of floc aging.

Successional dynamics of deep-sea nematode communities are shaped by environmental conditions, resource availability, and ecological processes such as species interactions, dispersal, and disturbance. This study investigates the in-situ response of free-living nematodes to artificial organic matter enrichment at the deep-sea floor in the Arctic Ocean. The experiment was conducted at 1265 m depth at the LTER HAUSGARTEN observatory in Fram Strait. We created azoic sediments with a grain size composition similar to natural deep-sea sediments and applied three treatments: (1) azoic sediment (control), (2) azoic sediment treated with fresh Phaeocystis , and (3) azoic sediment treated with decaying Phaeocystis . The organic content of the artificial sediments was adjusted to match that of natural sediments. The experimental setup was deployed for three months with a bottom lander and compared to natural sediment samples for reference. Despite similar organic carbon content, artificial sediments exhibited lower nematode abundance and diversity compared to natural sediments, indicating an early successional state dominated by opportunistic taxa. Organic enrichment influenced community composition, with fresh Phaeocystis favouring epistrate feeders and decaying Phaeocystis supporting later-stage colonisers. Natural sediments, characterized by long-term stability and organic accumulation, supported higher nematode abundance, functional diversity, and a balanced trophic structure. These findings indicate that a mature community requires more time to develop than the three-month duration of the experiment. Our findings emphasize the role of organic matter retention and long-term sediment accumulation in shaping deep-sea nematode communities and highlight the potential ecological consequences of anthropogenic-driven changes in organic matter deposition, which could affect deep-sea biodiversity and ecosystem resilience. • Artificial sediments had lower nematode abundance and were dominated by opportunistic genera, indicating early successional stages • Natural sediments supported a mature, diverse nematode community • Sediments enriched with fresh Phaeocystis favoured epistrate-feeding nematodes • Sediments enriched with decayed Phaeocystis favoured later-stage nematode colonisers

Regulation effect of polymeric and mineral additives on vermicomposting of biochemical tailings of kitchen wastes

Biogeochemical cycling of sulfur and iron constrains arsenic enrichment in groundwater: Microbial functionality and organic matter composition.

Wildfires are an increasingly important factor in boreal forest biome. The fire cycle have significant effects on the cycling of nutrients within and through an ecosystem. Past research shows that major elements, nutrients, and organic matter in stream water can be altered for decades after a wildfire. Here we examine how stream chemistry might be used to characterize biogeochemical effects of fire across the continuous permafrost taiga of the Central Siberia. By comparing the results of laboratory combustion of organic horizons, soil solution chemistry in burned and unburned watersheds, and stream chemistry in a chronosequence of watersheds with a well-described fire history, we assess possible proxies in stream water chemistry for wildfire severity and timing in this landscape. Our results suggest that the time since last wildfire can be estimated by sulfates (SO 4 2− ) and nitrates (NO 3 − ) concentrations, and that the soil active layer thickness (ALT, the soil depth at which soil thaws annually) increase by wildfires is reflected in bicarbonates (HCO 3 − ) concentrations. Phosphate (PO 4 3− ), although it is released from organic matter by combustion, is unchanged in stream water following fire. Chloride (Cl − ) produces a useful marker for hydrologic conditions at the time of sampling, allowing a relatively small number of stream water samples to be used to characterize past fire regime. Concentrations of SO 4 2− , NO 3 − and HCO 3 − in stream runoff can thus be used as a specific fingerprint of fire history in the northern taiga larch and birch forests of the Central Siberia, since an increase in their concentrations in stream runoff reflects fire occurrence in the catchment area. • Wildfires increase concentrations of major ions in pyrogenic organic layers, topsoil and streams. • Phosphorus is liberated by organic matter combustion, but retained in subsoil. • Wildfires affect stream HCO 3 − , SO 4 2− , Cl − and NO 3 − concentrations at decadal scales. • Stream bicarbonate can serve as a proxy for the active layer depth and wildfire timing • Sulfate in stream water is the most reliable indicator of time since fire disturbance in the catchments.

Volcanic speleothems are promising archives of organic matter (OM) in planetary analogue environments, offering valuable insights into past or extant microbial life and environmental conditions. In this study, we applied elemental analysis–isotope ratio mass spectrometry (EA/IRMS), analytical pyrolysis (Py-GC/MS), and pyrolysis-compound-specific isotope analysis (Py-CSIA) to characterize the molecular and isotope composition of four samples collected from the Corona Lava Tube system in Lanzarote (Canary Islands, Spain). This site, explored during the ESA PANGAEA-X astronaut training campaign, serves as a natural laboratory for Mars subsurface analogues. We investigated two distinct cave samples (a black, organic-rich microbial mat and a white, mineral-dominated deposit), along with overlying topsoil and Euphorbia balsamifera vegetation, to trace the origin, transformation, and preservation of OM in this extreme subsurface environment. Stable isotope data and compound-specific signatures revealed marked differences in carbon and hydrogen isotope compositions between surface- and cave-derived organics, indicating divergent biogeochemical pathways and microbial activity. Notably, ¹³C-enrichment in sterols and lignin-derived compounds within the cave matrix pointed to intense microbial processing, while δ ²H data reflected the incorporation of past meteoric water and diagenetic alteration. Our findings demonstrate the power of Py-CSIA for resolving biosignatures at the molecular level and underscore the diagnostic potential of isotope tools in volcanic subsurface systems. This approach provides a critical framework for future astrobiological exploration and life-detection strategies in Martian lava tubes, where subtle organic traces may offer the clearest evidence of habitability or life beyond Earth. • Py-CSIA enables unprecedented resolution in tracing organic matter in lava tubes • Microbial transformation of plant-derived organic matter in a nutrient-poor cave ecosystem • δ²H signatures suggest diagenetic alteration linked to ancient meteoric water • Pyrolysis-coupled isotope analysis offers high-resolution biosignature detection valuable for astrobiology

Effects of co-existing cations, anions, and organic matter on the selective removal of phosphate by lanthanum-1,4-benzenedicarboxylic framework

Unveiling colloid-mediated mobilization of Cd/As/Cr by low-molecular-weight organic acids in high geological background soils.

Distribution and potential provenance of metal nanoparticles in sediment core from Daya Bay, northeastern South China Sea.

Sustaining soil health is paramount for global food security, carbon sequestration, and ecosystem resilience, while traditional wet-chemistry analyses remain time-consuming and resource-intensive. Visible-Near InfraRed (vis-NIR) and X-ray Fluorescence (XRF) have emerged as rapid, cost-effective alternatives for monitoring key soil health parameters, especially fertility attributes. In parallel, supervised Machine Learning (ML) has revolutionized soil modeling by transforming complex spectral signatures into high-level soil features. Despite their outstanding performance, such AI-driven approaches often operate as ”black boxes”. In this context, this review situates the current landscape of soil fertility modeling via integrating ML with vis-NIR and XRF, particularly focusing on adopting explainability methods to make models more explainable and transparent. By systematically surveying studies from 2019 to June 2025 (315 articles), we found that carbon, organic matter, clay, pH, nitrogen, and sand are the most prevalent predicted parameters, reflecting their pivotal role in soil health assessment. Vis-NIR dominates as the sensing technology (especially in multi-country investigations) while XRF, despite its elemental sensitivity, requires testing in large-scale contexts. In modeling, there has been a transition from traditional linear regressors ( e.g. , MLR and PLS) to more advanced, non-linear learners such as neural networks, which impact models’ explainability. Explainability techniques have primarily been implemented at the global level (notably through informative coefficients and dimensionality reduction), whereas local explainers (sample-specific assignments) are scarcely employed. To offer a practical guide for selecting methods aligned with research goals and data characteristics, we leveraged eXplainable AI (XAI) core concepts to propose a taxonomy for categorizing explainability tools according to agnosticism, scope, timing, and transparency. In conclusion, achieving a balance among predictive performance, complementarity between data sources, and effective communication of model behavior—accomplished through close collaboration with domain experts and robust XAI practices—is essential for developing more practical and reliable soil fertility modeling strategies. • A review of ML and adopted explainability tools in soil fertility monitoring was conducted. • A shift toward employing advanced nonlinear models, especially deep learning, was noticed. • A balance between performance and explainability needs XAI solutions. • Enhancing model communication through explainability can make soil fertility modeling more trustworthy. • Explainability tools was arranged by nature, scope, workflow stage, and transparency by a new taxonomy proposal.

Coastal carbon cycle and budgets are significant drivers of regional climate change, generating widespread global attention. This study explored the spatial and seasonal variability of alkalinity biogeochemistry within a coastal aquifer-aquitard system in the Pearl River Delta, China. We measured physicochemical parameters including salinity, temperature, and pH, total alkalinity (TA), stable isotopes, cations, and anions of groundwater samples, which were collected every season using permanent multilevel groundwater sampling systems installed at three field sites of PRD. Results revealed that the elevated production of total alkalinity and dissolved inorganic carbon in the deltaic aquifer-aquitard system stemmed from sedimentary organic matter due to the presence of the aquitard formed during the Holocene marine transgressive event. Cluster analysis, incorporating various components of inorganic carbon and physical-chemical features, classified sources of TA in groundwater samples into four categories: modern weathering dominated, Holocene transgression dominated, late Pleistocene weathering dominated, and early Pleistocene weathering dominated. The study suggests that Holocene marine sediments act as dynamic biogeochemical reactors, supplying organic matters and influencing carbon cycles amidst complex hydrogeological and biogeochemical conditions.

Biological processes dominate the dynamic changes in the dissolved inorganic carbon ion equilibrium system of coastal wetlands under tidal influence.

Physicochemical and geotechnical characteristics of raw dredged sediments and the mechanical, durability and thermal properties of sediment-based earth materials: an overview

Silver-loaded granular activated carbon for fixed-bed drinking water treatment: antibacterial effect in both water and biofilm phases and impact on organic matter removal.

Synergistic iron ion and sulfate removal via chitosan-engineered yeast biosorbents.