2353 papers
This study demonstrates that biodegradable microplastics PBAT and PLA exert distinct and divergent effects on soil nitrogen cycling and microbial community structures, highlighting that their environmental risks are polymer-specific rather than uniform.
This study utilizes explainable machine learning on multi-source data to reveal that vegetation and carbon storage are critical cooling factors in Chicago's warming urban landscape, demonstrating that carbon conservation offers dual benefits for climate mitigation and heat reduction.
Using a dense network of low-cost sensors in South Florida's Everglades Agricultural Area, this study evaluated geospatial interpolation techniques for estimating PM2.5 from sugarcane burning, finding that while inverse distance weighting performed best individually, a dynamic approach selecting the optimal model daily provided the most robust exposure estimates for future health research.
This paper presents a reproducible open-data workflow using Sentinel-1 and Sentinel-2 satellite imagery to independently map the September 2024 Lang Nu debris avalanche in Vietnam, confirming its 0.66 km² extent and demonstrating its exceptional mobility (2.3 times the global mean) consistent with mechanisms of saturated deposit entrainment and velocity-weakening friction.
This study provides quasi-experimental evidence that Finland's METSO voluntary payment program effectively retains biodiversity-relevant forest structure by significantly avoiding clear-cutting and improving stand characteristics, thereby demonstrating the success of market-based incentives in addressing forest degradation beyond simple deforestation.
This study reveals that seasonal rising water tables can mobilize traditionally inaccessible iron-bound phosphorus from deep soil layers, suggesting that many landscapes currently considered phosphorus-poor may actually possess significant, dynamic nutrient reserves driven by redox fluctuations.
This study demonstrates that while incorporating mechanistic permafrost thaw feedbacks into the DICE 2023 model significantly increases projected global temperatures, the resulting welfare losses appear negligible under standard damage functions and discounting conventions, revealing that the model's insensitivity to ecological feedbacks stems from structural assumptions in its damage and discount parameters rather than the physical climate dynamics themselves.
This study demonstrates that in Chilean wetland soils, water repellency and pore structure recovery are coupled and depth-dependent, with topsoil exhibiting reversible behavior while subsoil undergoes irreversible changes due to drying beyond its historical matric potential range, a process primarily driven by organic carbon content.
This study reveals that water yield, soil carbon storage, and waterbird habitat functions in Qinghai–Tibetan Plateau alpine swamp meadows have changed asynchronously over the past three decades, with spatial co-occurrence of high values failing to predict temporal stability, thereby identifying specific future risk hotspots where high current multifunctionality faces imminent degradation under climate change.
This study develops and validates a census-tract-level logistic regression model using historical California earthquake data to effectively predict and prioritize spatial fire-following-earthquake ignition risks, demonstrating strong performance in both cross-validation and application to the USGS HayWired earthquake scenario.