Integrating mobile monitoring data with street view images (SVIs) holds promise for predicting local air pollution. However, algorithms, sampling strategies, and image quality introduce extra errors due to a lack of reliable references that quantify ...
Climate change is exacerbating rainstorms, increasing the risk of flooding and threatening urban sustainability, which could undermine climate action. Here, we propose a machine learning-based framework to assess heterogeneous risks and identify crit...
Polymers are widely produced and contribute significantly to environmental pollution due to their low recycling rates and persistence in natural environments. Biodegradable polymers, while promising for reducing environmental impact, account for less...
Machine learning (ML) is expected to bring new insights into the impact of organic structures on the reaction mechanisms in reactive oxygen species oxidation. However, understanding the underlying chemical mechanisms still faces challenges due to the...
Machine learning is an effective tool for predicting reaction rate constants for many organic compounds with the hydroxyl radical (HO). Previously reported models have achieved relatively good performance, but due to scarce data (<1400 records), the ...
Growing wildfire smoke represents a substantial threat to air quality and human health. However, the impact of wildfire smoke on human health remains imprecisely understood due to uncertainties in both the measurement of exposure of population to wil...
Polymeric membranes have been widely used for liquid and gas separation in various industrial applications over the past few decades because of their exceptional versatility and high tunability. Traditional trial-and-error methods for material synthe...
The biotoxicity of nanoplastics (NPs), especially from environmental sources, and "NPs carrier effect" are in the early stages of research. This study presents a machine learning-assisted "shrink-restricted" SERS strategy (SRSS) to monitor molecular ...
Environmental chemicals can enter the human body through various exposure pathways, potentially leading to neurotoxic effects that pose significant health risks. Many such chemicals have been identified as neurotoxic, but the molecular mechanisms und...
Electroactive biofilm (EAB) sensors have become pivotal in water quality detection and early ecological risk warnings due to their remarkable sensitivity. However, it is challenging to identify multiple toxicants in complex water bodies concurrently....