Environmental Health

Derivation of safety threshold for soil organic chemicals based on source-transport-fate dynamics in the soil-groundwater system: A case study of soil 1,2,3-trichloropropane in the Yangtze River Delta region, China.

1,2,3-Trichloropropane (TCP) is a persistent and highly toxic contaminant that poses substantial risks to groundwater systems. However, deriving groundwater-protective soil safety thresholds remains challenging because conventional empirical methods fail to adequately capture the spatial heterogeneity inherent in hydrogeological environments. A coupled "Ksw-AF-DF" modeling framework was developed ...

Machine Learning-Assisted Concentration-Independent Recognition of Neonicotinoids Based on Multienzyme-like Activities of FeCu Dual-Atom Nanozyme.

Residues of neonicotinoid insecticides (NEOs) pose serious threats to ecological systems and human health. Conventional nanozyme sensors often suffer from limited catalytic diversity and concentration-dependent response mechanisms, which lead to signal homogenization and cross-concentration misclassification. To address these limitations, we developed a Fe-Cu dual-atom nanozyme (FeCu DAzyme) exhib...

Vietnamese Odonata: bridging global biodiversity, ecological, and conservation gaps in a changing world.

Vietnam is a global hotspot, hosting 493 Odonata species, with ~95% evaluated by the IUCN. Odonata species play vital ecological roles in aquatic and ...

Source apportionment of pollution in the Tianjin Haihe river sluice based on the TCN-APCS-MLR model.

River pollution identification in complex watersheds like the Haihe River Sluice faces challenges due to temporal dynamics and nonlinear driving mecha...

Spatiotemporal characteristics and driving factors of coal-burning hotspots in Shandong Province revealed by multi-source data and machine learning.

Coal combustion emissions significantly contribute to air pollution in China, especially in the residential sector, where they are widely dispersed an...

Coupling bayesian optimization and multi-paradigm ensemble learning to predict lead remediation in microbially induced carbonate precipitation: From model performance to crystalline control windows.

Microbially Induced Carbonate Precipitation (MICP), recognized as a highly promising green remediation technology, exhibits lead (Pb) immobilization e...

Machine learning-driven QSAR models for the prediction of metabolic mechanisms and thyroid hormone-disrupting effects of emerging pollutants in the human body: a case study of bisphenol analogues.

Research on theoretical prediction methods for elucidating the reaction mechanisms and thyroid hormone-disrupting effects of emerging pollutants in th...

Multilayer Vertical Interactions of Air Pollution and Meteorological Drivers Revealed by a Unified Data-Driven Model.

Vertical distribution of atmospheric pollutants is critical for refined air quality management, yet continuous vertical observations and traditional n...

AI-guided multi-omics analysis identifies NPC1-modulated susceptibility to SARS-CoV-2 infection under PM2.5 exposure.

Exposure to airborne fine particulate matter (PM2.5) has been linked to increased risk of the severe acute respiratory syndrome coronavirus 2 (SARS-Co...

Raman spectra for plastics identification (RaSPI) and Raman maps for plastics identification (RaMPI) datasets.

Efforts to expedite accurate identification of environmental plastics pollution have strong focus on machine learning (ML) techniques. We published tw...

Deciphering environmental determinants of soil metals in dust-influenced arid soils through interpretable models across data-availability scenarios.

Accurate prediction of soil potentially toxic metals (PTMs) and identifying their relationships with environmental drivers is essential for environmen...

Precision occupational lead exposure assessment through medical-informed machine learning.

Precise assessment of occupational lead exposure remains a major global public health challenge, as existing assessment methods are limited by overrel...

Diving into AI? Exploring the Potential for AI to Tackle Complex Water Quality Challenges.

Managing risks from water pollution is central to public health, environmental quality, and economic prosperity worldwide. While improvements in water...

Optimal machine learning models and factors for global infectious diseases: An ecological analysis.

BACKGROUND: Infectious diseases are a major global public health challenge. Socioeconomic and environmental changes have complicated the situation, un...

Machine learning approach for heavy metal source identification and spatial distribution in coastal sediments of Tiruchendur, Southern India.

This research focuses on the global issue of heavy metal (HM) contamination in coastal systems and provides the first baseline investigation of the su...

Spatially Optimized Nutrient Management as a Climate-Resilient Strategy to Reduce Nitrogen Runoff from Global Croplands.

Nitrogen fertilizer, as an indispensable input in crop production, has played a crucial role in enhancing crop yields. However, the associated croplan...

SODNet: a scale-oriented detection network for efficient UAV-based sewage outfall detection.

Accurate identification of river sewage outfalls is crucial for effective water pollution control. Unmanned Aerial Vehicles (UAVs), with their high mo...

Exploring seasonal coastal water quality parameter interactions through the self-organizing map neural network in eastern Mediterranean: Lebanon as a case study.

Coastal water pollution poses significant environmental challenges, leading to severe ecological and public health consequences. Thus, new assessment ...

Immune gene MMP9 as a potential key mediator in TCDD exposure-associated atherosclerosis: An integrated study based on network toxicology and experimental validation.

BACKGROUND: 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a highly toxic, recalcitrant persistent organic pollutant with ubiquitous environmental dist...

Satellite-based detection of asbestos-cement roofs using WorldView-3 VNIR data: An affordable evaluation tool for sustainable management of hazardous building infrastructure.

Asbestos-cement (AC) roofing remains a critical concern for urban environmental health, particularly in cities where asbestos bans were implemented la...