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Environmental Monitoring

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Dynamic patterns and potential drivers of river water quality in a coastal city: Insights from a machine-learning-based framework and water management.

Journal of environmental management
River water quality continues to deteriorate under the coupled effects of climate change and human activities. Machine learning (ML) is a promising approach for analyzing water quality. Nevertheless, the spatiotemporal dynamics of river water quality...

Uncovering the features of industrial odors-derived environmental complaints and proactive countermeasures by using machine-learning.

Journal of environmental management
Industrial odor-derived environmental complaints pose an emerging and far-reaching challenge in cities worldwide with intensive industries. Developing effective odor complaint management strategies is essential for mitigating the public impact of ind...

Leveraging explainable machine learning for enhanced management of lake water quality.

Journal of environmental management
Freshwater lakes worldwide suffer from eutrophication caused by excessive nutrient loads, particularly nitrogen (N) and phosphorus (P) from wastewater and runoff, affecting aquatic life and public health. Using a large (1800 km) subtropical lake as a...

Traffic noise prediction model using GIS and ensemble machine learning: a case study at Universiti Teknologi Malaysia (UTM) Campus.

Environmental science and pollution research international
This study represents a pioneering effort to integrate geographic information systems (GIS) and ensemble machine learning methods to predict noise levels on a university campus. Three ensemble models including random forest (RF), gradient boosting (G...

Machine learning-assisted source tracing in domestic-industrial wastewater: A fluorescence information-based approach.

Water research
An emergency water pollution incident poses a significant risk to the proper functioning of wastewater treatment plants, particularly in domestic-industrial integrated facilities. Source tracing is recognized as an effective method to mitigate ongoin...

Riverbed litter monitoring using consumer-grade aerial-aquatic speedy scanner (AASS) and deep learning based super-resolution reconstruction and detection network.

Marine pollution bulletin
Underwater litter is widely spread across aquatic environments such as lakes, rivers, and oceans, significantly impacting natural ecosystems. Current automated monitoring technologies for detecting this litter face limitations in survey efficiency, c...

Plastic debris detection along coastal waters using Sentinel-2 satellite data and machine learning techniques.

Marine pollution bulletin
Few studies have effectively shown how to use satellites that gather optical data to monitor plastic debris in the marine environment. For the first time, floating macro-plastics distinguishable from seaweed are identified in optical data from the Eu...

Machine learning reveals dynamic controls of soil nitrous oxide emissions from diverse long-term cropping systems.

Journal of environmental quality
Soil nitrous oxide (NO) emissions exhibit high variability in intensively managed cropping systems, which challenges our ability to understand their complex interactions with controlling factors. We leveraged 17 years (2003-2019) of measurements at t...

Deep-learning and data-resampling: A novel approach to predict cyanobacterial alert levels in a reservoir.

Environmental research
The proliferation of harmful algal blooms results in adverse impacts on aquatic ecosystems and public health. Early warning system monitors algal bloom occurrences and provides management strategies for promptly addressing high-concentration algal bl...

Predicting plateau atmospheric ozone concentrations by a machine learning approach: A case study of a typical city on the southwestern plateau of China.

Environmental pollution (Barking, Essex : 1987)
Atmospheric ozone (O) has been placed on the priority control pollutant list in China's 14th Five-Year Plan. Due to their unique meteorological conditions, plateau regions contain high concentrations of atmospheric O. However, traditional experimenta...