AIMC Topic: Environmental Monitoring

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Distribution patterns and source contributions of emerging contaminants in urban wastewater systems: from pumping stations to wastewater treatment plants.

Environmental pollution (Barking, Essex : 1987)
Sewage pumping stations and wastewater treatment plants (WWTPs) serve as critical nodes through which emerging pollutants (ECs) migrate from urban and industrial sources into aquatic environments. However, research on the co-occurrence, source dynami...

Human activities and climate override local catchment characteristics in explaining long-term phytoplankton trends in prairie lakes.

The Science of the total environment
Lakes across the globe are experiencing growing ecological pressure from climate change and human activities. In prairie regions, these pressures often result in shifts in phytoplankton abundance, a key indicator of water quality. Yet identifying the...

Quantifying Aviation-Related Contributions to Ambient Ultrafine Particle Number Concentrations Using Interpretable Machine Learning.

Environmental science & technology
Ultrafine particles (UFP, < 100 nm) are abundantly emitted by aircraft, but quantifying their contributions to ambient particle number concentrations (PNC) is challenging due to confounding from local traffic and complex interactions between aircraf...

Predicting the Fate and Source of Groundwater PFAS in the Pearl River Delta Region Based on Machine Learning.

Environmental science & technology
Extensive investigations into the increasingly severe contamination of perfluoroalkyl and polyfluoroalkyl substances (PFAS) in groundwater are currently causing high costs and long duration. Machine learning provides useful tools for predicting the o...

Hydrogeochemical and machine learning evidences for release and attenuation mechanisms of chromium contamination in a partially PRB remediation of shallow groundwater.

Environmental pollution (Barking, Essex : 1987)
This study aimed to investigate the release and attenuation mechanisms of Cr(VI) in a shallow aquifer system and evaluate the remediation performance of a permeable reactive barrier (PRB) in central China. A hydrogeochemical and machine learning fram...

Machine learning-based assessment of land use change effects on land surface temperature fluctuations in Ho Chi Minh city, Vietnam.

Environmental monitoring and assessment
Sustainable urban development requires actionable insights into the thermal consequences of land transformation. This study examines the impact of land use and land cover (LULC) changes on land surface temperature (LST) in Ho Chi Minh city, Vietnam, ...

Delineation of groundwater potential zones using data-driven approaches: towards achieving sustainable groundwater management in drought-prone region of Eastern India.

Environmental monitoring and assessment
To a large extent, the food security and ecological balance of a region, particularly in agriculturally dominated areas, largely depend on the sustainable use and management of groundwater resources. However, in recent times, both natural and human-d...

Deconvoluting and Interpreting Nontargeted Chemical Data: A Data-Driven Forensic Workflow for Identifying the Most Prominent Chemical Sources in Receiving Waters.

Environmental science & technology
Chemical forensics aims to identify major contamination sources, but existing workflows often rely on predefined targets and known sources, introducing bias. Here, we present a data-driven workflow that reduces this bias by applying an unsupervised m...

Evaluation and Diagnosis of Regional Ammonia Emission Inventory in the Pearl River Delta Using Multisite NH Observations and Model Simulations.

Environmental science & technology
Ammonia (NH) has attracted increasing attention for its reduction potential in fine particulate matter mitigation, yet current NH emission inventories involve substantial uncertainties. Previous bottom-up NH inventories are usually constrained by sat...

Assessing biodegradability potential of organic chemicals in aquatic and soil environment through classification-based machine learning models developed in accordance with OECD standards.

The Science of the total environment
Information on the biodegradation potential of organic chemicals in the ecosystem helps us analyze their persistence, bioaccumulation, and toxicity (PBT) behaviour. The environment is exposed to many chemicals from various sources, both intentionally...