📄 earth_science

Mercury use on the artisanal gold mining site at Gnikpière, Burkina Faso

This study of the Gnikpière artisanal gold mining site in Burkina Faso reveals that despite high awareness of mercury risks among miners, the widespread use of unprotected handling and open-air burning practices has resulted in significant soil contamination, particularly at milling sites, while water samples remained below detection limits.

Alice Rayim Wende NARE, Ouedraogo Issa, Moussa Bouboucari2026-08-15
📄 earth_science

Application of Multi ML-Model for Multi-Scale Meteorological Drought Monitoring under CMIP6-Climate Scenario in Data-Scarce Semi-Arid Regions

This study demonstrates that the Gaussian Process Regression (GPR) model, when applied to bias-corrected CMIP6 data at a 6-month scale, effectively forecasts meteorological drought in Iran's semi-arid Karkheh Hydrosystem, revealing that while longer time scales show wetter trends, the pessimistic SSP585 scenario poses significantly higher risks for extreme drought events compared to the more stable SSP126 scenario.

mohammadnabi jalali, Sahar Abdollahei, Bahareh Bastanfard, Zakeyeh aftabi, Morad KavianiRad2026-08-15
📄 earth_science

Satellite-Based Assessment of Air Pollution Dynamics and Land Surface Characteristics in Riyadh, Saudi Arabia Using Sentinel-5P, MODIS, and Google Earth Engine

This study utilizes multi-source satellite data and Google Earth Engine to analyze the spatiotemporal dynamics of air pollutants and land surface characteristics in Riyadh from 2018 to 2025, revealing that while seasonal meteorological conditions and urban greening influence pollution patterns, emission intensity and atmospheric processes remain the dominant controlling factors.

Fahad Alshehri, Hazem Abd El-Hamid2026-08-15
📄 earth_science

Soil nitrogen distribution, vertical migration, and leaching vulnerability in a typical shallow soil mountainous catchment: Evidence from the Chaohe River catchment, northern China

This study reveals that in the shallow-soil Chaohe River catchment, agricultural nitrogen is primarily enriched in surface layers with significant leaching vulnerability due to limited deep storage capacity, driven mainly by fertilizer inputs and mineralization while being positively regulated by soil sand content and negatively by pH.

Yi-Bo zhang, Yao-Qi Gong, Chen-Yang Shou, Yu-Lian Yu, Lei Wei, Shuang Song, Peng-Yu Zhang, Fu-Jun Yue, Xiao-Long Liu2026-08-15
📄 earth_science

Experimental setup for measuring thermal conductivity of rocks under water-saturated conditions at increasing temperatures using the Transient Plane-Source technique

This study introduces a novel experimental setup using the Transient Plane Source technique to directly measure the thermal conductivity of water-saturated sandstone at elevated temperatures, revealing a temperature-dependent decrease in conductivity and highlighting the limitations of relying on dry-state data or mixing models for geothermal reservoir assessments.

Maëlle Brémaud, Neil M. Burnside, Zoe K. Shipton, Sven Fuchs, Robert Peksa2026-08-15
📄 earth_science

Large Language Model-facilitated national review on the use of ecological tools and processes in Environmental Impact Statements (EIS) in the U.S. with demonstrated use cases for environmental planners, legal practitioners, and researchers

This paper presents a large-scale review of over 2,000 U.S. Environmental Impact Statements using a customized Retrieval-Augmented Large Language Model pipeline to create a centralized ecology data store that reveals regional and sectoral trends in ecological tool usage and demonstrates its practical utility for environmental planners, legal practitioners, and researchers through specific case studies.

Dahn-young Dong, Lauren Schramm, Kris Thoemke, Tuoya Saren, Sean Schoville2026-08-15
📄 earth_science

Warming driven intensification of Heat–Wet Alternations over South Indian Peninsula (1981–2024): Diagnosis and Machine Learning based Predictive Modeling

This study reveals that the South Indian Peninsula has experienced a significant warming-driven intensification of Heat–Wet Alternations since 1981, characterized by increased frequency and non-stationary variability linked to planetary warming and reorganized climatic modes, while also demonstrating the efficacy of a machine learning model in predicting these compound extremes based on antecedent local heat.

Micky Mathew, K Sreelash, Jeenu Mathai, Alice Thomas, Rajat Kumar Sharma, D Padmalal2026-08-14