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Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 &#x2265; 0.988, prediction set root mean square error (RMSEP) &#x2264; 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil

Mapping Wastewater Pathogens and Their Associated Environmental and Public Health Risk Factors: A Systematic Review and Meta-Analysis.

BACKGROUND: Wastewater-based epidemiology (WBE) has emerged as a critical tool for public health surveillance, yet its application across diverse pathogens and geographical settings remains inconsistent. This systematic review synthesizes global evidence on wastewater surveillance to identify associated risk factors. METHODS: Following PRISMA 2020 guidelines (PROSPERO: CRD420261297382), a systematic search was conducted across PubMed, Scopus, Google Scholar, and Web of Science for studies published between 2000 and 2025. RESULTS: Thirty-nine peer-reviewed studies were included. The evidence base is geographically skewed toward the European Region (48.7%) and the Americas (23.1%), with significant underrepresentation in LMICs. Viruses were the primary biological target (89.7%), followed by bacteria (7.7%) and parasites (2.6%). A proportion meta-analysis of 31 eligible studies demonstrated a pooled wastewater pathogen detection prevalence of 62% (95% CI: 47.5-74.6%), with the European Region yielding the highest regional estimate (73%) and the African Region the lowest (8.3%). Conventional PCR and sequencing methods showed higher pooled detection rates (92.4% and 90.1%, respectively) than RT-qPCR (47.9%). CONCLUSION: WBE provides a robust early-warning system indicating a need for broader pathogen diversity, incorporating bacterial and parasitic surveillance and expansion into rural and resource-limited regions.

Contamination

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans

Application of causal discovery of factors driving dissolved oxygen in estuarine environments.

Dissolved oxygen (DO) concentrations in estuarine bottom waters are a manifestation of multiple, interacting physical and biogeochemical processes, yet identifying their independent contributions remains challenging. Here, we analyze monthly water quality monitoring data from eight stations across Long Island Sound from 1994 to 2022 using a causal discovery framework (PCMCI+) and transformation of forcing variables. Our goal is to identify and isolate variables that causally influence bottom DO and improve predictive models by minimizing overfitting and multicollinearity. PCMCI+ reveals surface-layer temperature as the most important and consistent negative driver of bottom DO, followed by stratification. Wind events exhibit only brief relief by advection and mixing, while river discharge shows no direct causal link to DO, making it less influential than previously thought. Biogeochemical variables, including chlorophyll-a (Chl-a), nitrate and nitrite, and particulate carbon, influence DO through both contemporaneous and time-lagged pathways, often with signs that shift depending on the process. The derived models were evaluated by comparing skill scores, mean squared error, and Akaike Information Criterion. Both model types perform well, with coefficient of determination values exceeding 0.90 at multiple stations using only 3-5 predictors. Our analysis reveals that the best causal predictors are surface-layer temperature, stratification, Chl-a, and particle carbon. This approach provides a scalable framework for improving prediction models and understanding the mechanistic links that control the seasonal variability of DO in estuarine systems.

Estuaries

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5&#x200b; concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution

Urban stormwater infrastructure as a microplastic superhighway: a critical review of transport dynamics, modelling, and mitigation across pavements and drainage networks.

This review examines the transport, fate, modelling, and mitigation of Microplastics (MPs) in urban stormwater infrastructure, with emphasis on pavements, runoff pathways, micro-drainage, and macro-drainage systems. Following a systematic review approach, more than 1000 records were screened and approximately 50 core studies were retained when they addressed urban stormwater or drainage-related MP transport with adequate methodological reporting; marine-only studies and biological-effect studies without direct relevance to transport processes were excluded. The evidence shows that stormwater systems function not merely as passive conduits but as dynamic reactive transport systems with temporary storage, where particle mobilisation, sedimentation, resuspension, and temporary retention regulate MP export. Road surfaces, especially high-traffic areas, are major reservoirs of tyre wear, road-marking, atmospheric, and litter-derived particles that are rapidly mobilised during rainfall. Conventional grab sampling may underestimate MP loads, which in some cases exceed treated wastewater effluent loads by up to six-fold. Drainage structures such as manholes can immobilise up to 17.3% of near-neutrally buoyant particles, while biofouling and aggregation may shift buoyant polymers from wash-load to bedload. Mitigation systems, including permeable pavements, bioretention, wetlands, and technical inserts, can achieve high removal of coarse MPs, but performance declines for fine particles below 100&#xa0;&#xb5;m. The review highlights the need for standardised flow-proportional sampling, physically informed modelling, and treatment-train strategies targeting both surface sources and in-network storage.

Microplastics

Long-term petroleum pollution alters soil microbial communities via electron transfer capacity: Evidence from a 35-year chronosequence.

Petroleum pollution poses a serious threat to soil ecosystems, especially in areas surrounding oil wells, where contamination should not be overlooked. Through a 35-year longitudinal study of soils surrounding oil wells, we demonstrate that petroleum hydrocarbons accumulate predominantly in the top 10 cm of soil, reducing the electron acceptor capacity (EAC) by 61.59 % (from 12.68 to 4.87 &#x3bc;mole-/gC) and decreasing the electron transfer capacity (ETC) by 43 %. Structural equation modeling identified ETC as the critical mediator of microbial community shifts, with EAC playing a pivotal role in sustaining redox processes. Notably, hydrocarbon accumulation triggered a microbial succession: The abundance of Actinomycetota (including genera Rhodococcus, Arthrobacter, and Rubrobacter) showed the most significant fluctuations within 2 years, while Pseudomonadota (genera Methylobacter, Thiobacillus, and Pseudomonas), which were dominant in uncontaminated soils, decreased markedly during this period. This transition coincided with peak microbial dysbiosis (microbial dysbiosis index in 2022 reached 31.41 times that of controls). Within two to four years following mild petroleum stress, the bacterial community established a new structural configuration, revealing a crucial window for ecological recovery. The coupling between ETC reduction and microbial succession highlights the pivotal role of electron flux in soil recovery. Our findings establish a mechanistic framework for ETC-targeted restoration strategies to enhance bioremediation in petroleum-contaminated soils.

Soil Microbiology

Spore-forming Clostridia as overlooked determinants of microbial risk in wastewater reuse systems.

Using treated municipal wastewater for crop irrigation is a key strategy to combat drought-induced water scarcity. However, current wastewater reclamation standards systematically underestimate risks from spore-forming pathogens. As highlighted in a recent minireview by A. Mrozinski, C. Le Mar&#xe9;chal, and E. Topp in Applied and Environmental Microbiology (92:e00173-26, 2026, https://doi.org/10.1128/aem.00173-26), Clostridioides difficile and Clostridium perfringens survive conventional disinfection, persist indefinitely in agricultural soils, and harbor critical antibiotic resistance genes. To safeguard the food supply and protect public health, regulatory frameworks must shift from relying solely on standard vegetative bacterial indicators and include monitoring resilient, spore-forming pathogens.

Clostridium

Effects of aerosol aging on composition and light-absorbance of nitrogen-containing organic compounds: Evidences from ultra-high-resolution mass spectrometry analysis.

Nitrogen-containing organic compounds (NOCs) are key components of particulate matter (PM), but their compositional evolution and light-absorbing properties during atmospheric aging remain poorly understood. In this study, ultra-high-performance liquid chromatography coupled with Orbitrap mass spectrometry was used to semi-quantitatively analyze 59 PM1 samples collected in Shanghai. NOCs accounted for 31 % and 64 % of the detected species in negative (ESI-) and positive (ESI+) ionization modes, respectively. Atmospheric aging significantly reduced the molecular diversity of polar organics, with both the number and mass concentration percentages of CHON- compounds showing significant negative correlations with aging degree. Van Krevelen analysis demonstrated a decrease in the number of carboxylic-rich alicyclic molecules and their CHON- contributions during the aging process (from 37.7 % in fresh samples to 21.2 % in aged samples). CHN+ compounds, a major NOCs group in ESI+ mode, also decreased with aging. Correlation analyses involving the Bep/(Bep+Bap) ratio, relative humidity, and mass absorption efficiency at 365 nm revealed a decline in light absorption capacity with aging, suggesting aqueous-phase oxidation as a dominant aging mechanism. CHON- and CHN+ compounds were identified as the principal light-absorbing constituents in PM1. This work provides new insights into the aging-induced transformations of NOCs in urban PM1, and their changing role in light absorption, highlighting the need for further investigation of the aging mechanisms of NOCs.

Aerosols

Marine air promotes structural compaction and coating growth of soot aerosols after long-range transport from East Asia.

Soot aerosol, a key global warming contributor, undergoes morphological and chemical transformations during atmospheric transport, particularly in humidified marine environments. This study investigates morphology, mixing state, and aging mechanisms of soot particles collected in the Bohai Sea and Yellow Sea. Transmission electron microscopy analyses reveal that coated soot particles dominate the marine atmosphere, accounting for over 98 % of soot-containing particles, with a mean mixing state index (&#x3c7;) of 0.83. The fractal dimension (Df) of soot particles is 1.84 &#xb1; 0.05 in the Northern Yellow Sea, 1.90 &#xb1; 0.08 in the Bohai Sea, and 1.96 &#xb1; 0.07 in the Southern Yellow Sea, indicating structural compaction during long-range transport. Correspondingly, the average Dp/Dcore ratios (particle to core size ratio) are 5.3 in the Bohai Sea, 4.2 in the Northern Yellow Sea, and 3.9 in the Southern Yellow Sea. Notably, those ratios are higher in marine environments compared to those observed during continental regional transport from northern to southern China (3.54), suggesting enhanced coating growth in humid marine air. The results highlight the important role of marine atmospheres in accelerating soot aging, which in turn leads to significantly stronger light absorption compared to soot in continental air. Our results highlight the necessity of incorporating compact morphologies, uniform mixing states, and thick coatings into optical models for accurate radiative forcing simulations.

Aerosols

Degradation of a graphene-reinforced polyamide by fungi: When culture conditions matter.

The large-scale production, marketing and disposal of polymer-based graphene products can lead to the dispersal of graphene-enriched plastic particles into terrestrial ecosystems, where they might accumulate if not degraded by organisms. The objective of this work is to test the degradability and compatibility of one polyamide-6 polymer reinforced with reduced graphene-oxide (PA6-rGO) and its base constituents (polyamide-6, PA6; reduced graphene oxide, rGO) using mono- and co-cultures of two lignin-degrading fungi (Bjerkandera adusta and Morchella esculenta) grown under different nutrient conditions. Fungal (co-)cultures were exposed to pure rGO or abraded powders of PA6 and PA6-rGO in two different liquid media, and monitored over time for biomass growth, H2O2 production, and activity of two lignolytic enzymes (i.e., Laccase, Lac, and Lignin peroxidase, LiP). The changes in polyamide structure were evaluated by proton nuclear magnetic resonance and mass spectrometry, and changes in rGO were evaluated by Raman spectroscopy. The materials had no effect on fungal growth. PA6 increased Lac secretion only in low nutrient medium, while PA6-rGO slightly suppressed LiP activity. Only M. esculenta promoted polyamides oxidation when cultured in a low nutrient medium, as evidenced by a change in mass distribution values (m/z: 400-420) and the appearance of a new resonance peak (at 5.37 ppm). Lignolytic exudates in co-cultures low in nutrients caused a greater change in rGO, as shown by the increase in the ID/IG ratio. The degradation of rGO, PA6 and PA6-rGO depended on culture conditions.

Graphite

Towards microplastic bioremediation: Fungal degradation of pristine and pretreated high-density polyethylene and polystyrene.

Microplastic (MP) contamination has become a significant ecological issue because of its enduring existence in the ecosystem and its possible negative impacts. Therefore, using degrading strategies to eliminate these stubborn polymers has been a subject of scientific research. However, the currently used degradation methods are relatively inefficient. Given the pervasiveness of High-Density Polyethylene (HDPE) and Polystyrene (PS) and their resistance to biodegradability, disposal strategies are critical and must be addressed. This manuscript examines the biodegradation of pristine and UV-treated HDPE and PS MPs by Aspergillus flavus species in minimal growth media over 70 days. The maximum weight loss observed at 70 days for pristine HDPE and PS in sole carbon source (SCS) media was (29.33 &#xb1; 0.28) % and (17.67 &#xb1; 0.35) %, respectively. Whereas, for UV-treated HDPE and PS MPs, the % weight reduction was (33 &#xb1; 0.21) % and (25 &#xb1; 0.19) %, respectively. UV-treated MPs exhibited greater weight reduction, as UV induced oxygenated functional groups enhance polymer susceptibility to enzymes, thereby promoting biodegradation. HDPE MPs typically show a higher proportion of particles in the lower size range compared to PS MPs. This assertion was based on the weight loss, particle size distribution, and SEM analysis. Furthermore, chemical changes were evaluated using Fourier transform Infrared Spectroscopy (FTIR) analysis, which also displayed chemical oxidation occurring during biodegradation. Liquid Chromatography-Mass Spectrometry (LC-MS) results indicate that UV pretreatment enhances biodegradability by promoting chain scission. These findings further suggest that this fungus's natural and ubiquitous occurrence in terrestrial and marine environments may actively contribute to MP biodegradation while requiring few nutrients.

Microplastics

Coupling of spectroscopy and nitrogen-oxygen isotopes unveils the mechanisms of dissolved organic matter and nitrate pollution in lakes within the agro-pastoral transition zone.

Lakes in arid and semi-arid regions are subjected to severe ecological stress, such as organic pollution, eutrophication, and salinization, due to climate change and human activities. This study investigates Chagannur Lake, a typical arid-region lake that is representative and ecologically sensitive in Northern China's agro-pastoral ecotone, to uncover its pollution characteristics and mechanisms. We employed fluorescence spectroscopy and stable isotope analysis to trace dissolved organic matter (DOM) and nitrate sources. The DOM composition was dominated by microbial metabolic byproducts and protein-like substances, suggesting that microbial processes are key to organic matter transformation. Source apportionment revealed that pollutants primarily originated from livestock and poultry manure (37.6 %), agricultural fertilizers (35.6 %), and soil erosion (24.7 %), with agricultural fertilizers contributing most significantly in the Gogstai River (63.3 %). A structural equation model (SEM) coupling spectral and mass spectrometric data revealed that microbial transformation significantly impairs the lake's self-purification capacity, thereby promoting pollutant accumulation (path coefficient = 0.91,*p < 0.05). Moreover, microbial processes link endogenous and exogenous pollution, a mechanism effectively traced by isotopic and fluorescence indices (path coefficient = 0.55, &#x204e;&#x204e;p < 0.01). These findings enhance the understanding of pollution sources and transformation mechanisms in arid-region lakes and offer foundational theoretical support for policymakers engaged in pollution control strategies.

Lakes

Three-dimensional source apportionment and quantitative characterization of horizontal and vertical transport fluxes of O3 and its precursors in the Beijing-Tianjin-Hebei region, China.

Persistent surface ozone (O3) pollution in the Beijing-Tianjin-Hebei (BTH) region is driven by coupled precursor emissions and multi-scale transport, yet its altitude-dependent transport and source contributions remain insufficiently quantified. Here we integrated the Weather Research and Forecasting and the Comprehensive Air Quality Model with Extensions with the Ozone Source Apportionment Technology and a quantitative transport-flux framework to characterize three-dimensional source apportionment and horizontal/vertical fluxes of O3, Volatile Organic Compounds&#x200c; (VOCs), and Nitrogen Oxides (NOx) across dynamic meteorological scenarios. Simulations showed that VOCs and NOx were dominated by local emissions near the surface (73.61 %-82.18 %), whereas surface O3 was primarily controlled by regional transport, with local contributions of only 11.01 %-13.75 %. Notably, the transport dominance further strengthened with altitude, exceeding 93 % at 1.8 km. Industrial and transportation emissions together contributed more than 75 % of precursor emissions and account for approximately 80 % of O3 formation, while favorable/unfavorable meteorological years modulated long-range transport efficiency and the vertical distribution of contributions. Horizontal flux analysis highlighted three major pathways (Northwest-Southeast, Southeast-Northwest, and Southwest-Northeast), with Shijiazhuang serving as a critical pollutant "sink" across altitude layers. Vertical fluxes revealed an altitude transition near 600 m: net downward transport dominated below 600 m, whereas enhanced summer convection promoted upward transport above 600 m. These results support altitude-dependent, scenario-specific strategies for coordinated regional O3 mitigation in the BTH region.

Ozone

Nitrogen sources and concentrations shape algal odor compounds: Key drivers of &#x3b2;-cyclocitral and &#x3b2;-ionone in water bodies of the lower Yangtze River.

Taste and odor (T&O) compounds derived from cyanobacterial blooms pose escalating threats to freshwater security worldwide, yet the drivers of specific T&O metabolites remain poorly constrained. Here, we investigated the dual effects of nitrogen (N) sources and concentrations on the production of &#x3b2;-cyclocitral and &#x3b2;-ionone, two algal-derived T&O compounds, through integrated field surveys (54 sites across lakes and rivers) in the eutrophic lower Yangtze River, China, and laboratory cultivation of typical cyanobacteria (Microcystis aeruginosa and Pseudanabaena cinerea). Our field data revealed that the concentrations of &#x3b2;-cyclocitral and &#x3b2;-ionone in lakes and rivers were not significantly different, but increased with the trophic level index. Redundancy analysis and Mantel analysis showed that Microcystis and Pseudanabaena were potentially dominant contributors to &#x3b2;-cyclocitral and &#x3b2;-ionone in the water column. Structural equation modeling and variation partitioning analysis showed that enhanced nitrate (NO3--N) significantly promoted the production of these compounds. Laboratory experiments demonstrated that inorganic N (NaNO&#x2083;) maximized total T&O yields by promoting algal biomass, whereas organic N (urea and glutamic acid) elevated the T&O production per unit biomass by 1.5- to 9.5-fold. Notably, Pseudanabaena exhibited a 2.3-fold higher &#x3b2;-ionone yield than Microcystis, with greater sensitivity to N concentrations. Our study highlights the critical role of nitrogen pollution, both source and concentration, in the production of T&O compounds by phytoplankton and provides reference data for managing T&O issues in rivers and shallow lakes.

Norisoprenoids

Antarctic Peninsula soil carbon stock and efflux: A complex interplay of soil properties and heavy metals.

This study establishes a quantitative framework for understanding surface soil carbon dynamics and ecosystem connectivity in Fildes Peninsula and Ardley Island, King George Island, South Shetland Islands, Antarctic Peninsula. The mean soil organic carbon (SOC) stock across all study sites was 1.10 &#xb1; 1.93 kg C/m&#xb2;. Restricting net carbon balance analysis to Fildes Peninsula, where soil respiration (Rs) data were available, yielded a site-specific SOC stock of 0.45 &#xb1; 0.45 kg C/m&#xb2;. Scaling Rs to a realistic 120-day active season and assuming stable SOC stocks resulted in estimated annual carbon loss of 15 g C/(m2&#xb7;yr), equivalent to 3.3 % of standing SOC. Comprehensive sensitivity analyses spanning plausible winter respiration (0 %-20 % of summer rates) and annual change in SOC stocks (-1 %-2 %) consistently supported a net carbon sink, with turnover rates constrained to 3.3 %/yr-4.7 %/yr. Principal component analysis showed that ornithogenic processes as the dominant control on SOC, total nitrogen (TN), zinc (Zn), copper (Cu), and cadmium (Cd) provide a clear multivariate signature of marine-derived nutrient, while Pb was decoupled from this gradient and associated instead with fine-particle size controls. These results reveal dual but independent drivers of soil metal enrichment in this region. Despite their limited spatial extent, ornithogenic soils store disproportionately large carbon pools. Overall, this integrated analysis reveals how marine-terrestrial subsidies regulate Antarctic carbon cycling and provides a quantitative and reproducible framework for assessing carbon dynamics under ongoing climate change.

Antarctic Regions

Biomass burning contributions to Mexico City's atmospheric CO2 estimated using a multi-isotope approach.

Fossil fuel combustion dominates anthropogenic emissions worldwide; however, special attention should be addressed to biomass burning, since it is an increasingly important contributor under warmer, drier fire-weather conditions exacerbated by climate change. These emissions could impact the atmospheric composition of heavily urbanized environments. To assess the influence of biomass burning, along with fossil fuels combustion and soil and plant respiration on Mexico City's atmospheric composition, we conducted a year-long (December 2023-December 2024) isotopic monitoring of atmospheric CO2, combining radiocarbon (&#x394;14C), CO2 stable isotopes (&#x3b4;13C, &#x3b4;18O), and CO/CO2 ratios. Once defined the isotopic signatures and the characteristic CO/CO2 that describe the sources, we performed Monte Carlo simulations under two tracer modalities (&#x394;14C + CO/CO2 and &#x394;14C + CO2 stable isotopes) for source apportionment. Results show that during the dry season, particularly in March-April, atmospheric &#x394;14C values approached and overlapped background levels despite Mexico City's fossil-fuel dominance, indicating enhanced non-fossil inputs. Moreover, backward HYSPLIT trajectories supported that these elevated &#x394;14C values coincided with regional wildfire activity. Monte Carlo results attributed up to &#x223c;34 %-60 % of local CO2 to biomass burning in April, followed by March with contributions of &#x223c;31 %-49 %. Since these biomass burning figures contrast with the official emissions inventory of Mexico City metropolitan area, which assigns <1 % of total CO2 emissions to biomass burning, this study could exhibit the emissions inventory underestimation of this source, and thus, the need to reassess and incorporate top-down isotopic constraints in fire-affected urban regions.

Mexico

A novel urease-producing strain effectively induces cadmium biomineralization under low-temperature stress.

Microbially induced carbonate precipitation (MICP) has been widely used to immobilize Cadmium (Cd) in contaminated soils in mining-affected regions. However, its remediation efficacy under low-temperature stress, as well as the nucleation process that regulates Cd biomineralization via carbonate precipitation by psychrophilic bacteria, has yet to be investigated. Here, we isolated Pseudomonas sp. J-6, a novel urease-producing strain from tailings in high-altitude cold regions, exhibiting unparalleled cold adaptability at 5 &#xb0;C and achieving 95.85 % Cd removal efficiency by MICP at 10 &#xb0;C. Furthermore, the coprecipitation process of Ca1-xCdxCO3 was clarified through the continuous observation of the precipitates after the low-temperature MICP reaction. The crystal morphology transitioned from loose vaterite in the early stage to a dense square-block morphology in the middle stage. Cd2+ progressively shifted from a surface-bound state to lattice incorporation, ultimately resulting in the formation of stable Cd-substituted calcite crystals. In this process, low temperatures led to the formation of larger, highly ordered Cd-substituted calcite crystals, thereby strengthening Cd sequestration and its long-term stability. In addition, under low-temperature stress, Pseudomonas sp. J-6 induced MICP reaction decreased the bioavailable Cd in alpine slag soil by 44.85 % and enhanced physical properties. In the freeze-thaw cycles, the remediation efficiency remained stable. This study clarified the biomineralization potential in high-altitude cryogenic environments and the nucleation process of Cd biomineralization by psychrophilic bacteria-induced carbonate precipitation, filling a critical research gap in its application under extreme conditions and highlighting its promise for sustainable remediation of heavy metal pollution under low-temperature stress.

Cadmium