AIMC Topic: Ozone

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Using wavelet-feedforward neural networks to improve air pollution forecasting in urban environments.

Environmental monitoring and assessment
The paper presents the screening of various feedforward neural networks (FANN) and wavelet-feedforward neural networks (WFANN) applied to time series of ground-level ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM10 and PM2.5 fractions...

Soil and litter emission sources as important contributors to ozone production from volatile organic compounds in island tropical forests.

Environmental research
While studies have confirmed that volatile organic compounds (VOCs) emitted directly by tropical island forest vegetation significantly influence ozone (O) production and climate change through atmospheric oxidation processes, the environmental effec...

Coastal ozone dynamics and formation regime in Eastern China: Integrating trend decomposition and machine learning techniques.

Journal of environmental sciences (China)
Machine-learning is a robust technique for understanding pollution characteristics of surface ozone, which are at high levels in urban China. This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to i...

Machine Learning-Assisted Discovery of Bimetallic Oxides for Highly Efficient Catalytic Ozonation.

Environmental science & technology
Catalytic ozonation stands out as an effective process in the advanced treatment of industrial wastewater, where heterogeneous catalysts play a pivotal role. Here, by screening 1603 bimetallic oxides via machine learning (ML), a pioneering ZnCuO was ...

Revolutionizing Satellite Real-Time Air Pollution Alerts through New On-Orbit System-on-Chip Technology.

Environmental science & technology
Exposure to abnormally high concentrations of particulate matter and ozone can cause severe harm to human health, highlighting the need for real-time satellite monitoring to enable rapid responses and timely warnings. However, the existing methods fo...

Using machine learning to unravel chemical and meteorological effects on ground-level ozone: Insights for ozone-climate control strategies.

Environment international
In the context of climate change, various countries/regions across East Asia have witnessed severe ground-level ozone (O) pollution, which poses potential health risks to the public. The complex relationships between O and its drivers, including the ...

Deep learning-based forecasting of daily maximum ozone levels and assessment of socioeconomic and health impacts in South Korea.

The Science of the total environment
Accurate forecasting of ground-level ozone (O) is essential for assessing its public health and socioeconomic impacts. This study evaluates the performance of three deep learning models-Deep Convolutional Neural Networks (Deep-CNN), Long Short-Term M...

Mapping Regional Meteorological Processes to Ozone Variability in the North China Plain and the Yangtze River Delta, China.

Environmental science & technology
High-concentration ozone threatens human health and ecosystems, modulated by dynamic, multiscale meteorological processes. Existing machine learning studies for ozone prediction rarely incorporate the spatiotemporal evolution of regional meteorologic...

Distribution characteristics of volatile organic compounds and its multidimensional impact on ozone formation in arid regions based on machine learning algorithms.

Environmental pollution (Barking, Essex : 1987)
Volatile Organic Compounds (VOCs) are key components of atmospheric pollution and play a critical role in ozone (O) formation. Understanding their distribution and pollution sources is essential to grasping the multifaceted impact of VOCs on O produc...

Amazon's climate crossroads: analyzing air pollution and health impacts under machine learning-based temperature increase scenarios in Northern Mato Grosso, Brazil.

Environmental geochemistry and health
Air pollution has long been a public health concern in South America, now increasingly linked to climate change. In Brazil, this issue is particularly acute in smaller cities with limited monitoring infrastructure. Sinop, located in the Amazon biome ...