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Ozone

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New Deep Learning Model to Estimate Ozone Concentrations Found Worrying Exposure Level over Eastern China.

International journal of environmental research and public health
Ozone (O3), whose concentrations have been increasing in eastern China recently, plays a key role in human health, biodiversity, and climate change. Accurate information about the spatiotemporal distribution of O3 is crucial for human exposure studie...

Feature selection for global tropospheric ozone prediction based on the BO-XGBoost-RFE algorithm.

Scientific reports
Ozone is one of the most important air pollutants, with significant impacts on human health, regional air quality and ecosystems. In this study, we use geographic information and environmental information of the monitoring site of 5577 regions in the...

Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter.

Environmental pollution (Barking, Essex : 1987)
From hourly ozone observations obtained from three regions⸻Houston, Dallas, and West Texas⸻we investigated the contributions of meteorology to changes in surface daily maximum 8-h average (MDA8) ozone from 2000 to 2019. We applied a deep convolutiona...

Estimation of surface ozone concentration over Jiangsu province using a high-performance deep learning model.

Journal of environmental sciences (China)
Recently, the global background concentration of ozone (O) has demonstrated a rising trend. Among various methods, groun-based monitoring of O concentrations is highly reliable for research analysis. To obtain information on the spatial characteristi...

Deep learning mapping of surface MDA8 ozone: The impact of predictor variables on ozone levels over the contiguous United States.

Environmental pollution (Barking, Essex : 1987)
The limited number of ozone monitoring stations imposes uncertainty in various applications, calling for accurate approaches to capturing ozone values in all regions, particularly those with no in-situ measurements. This study uses deep learning (DL)...

Cooperative simultaneous inversion of satellite-based real-time PM and ozone levels using an improved deep learning model with attention mechanism.

Environmental pollution (Barking, Essex : 1987)
Ground-level fine particulate matter (PM) and ozone (O) are air pollutants that can pose severe health risks. Surface PM and O concentrations can be monitored from satellites, but most retrieval methods retrieve PM or O separately and disregard the s...

Development of a recurrent spatiotemporal deep-learning method coupled with data fusion for correction of hourly ozone forecasts.

Environmental pollution (Barking, Essex : 1987)
Ambient ozone (O) predictions can be very challenging mainly due to the highly nonlinear photochemistry among its precursors, and meteorological conditions and regional transport can further complicate the O formation processes. The emission-based ch...

Combining physical mechanisms and deep learning models for hourly surface ozone retrieval in China.

Journal of environmental management
As surface ozone (O) gains increasing attention, there is an urgent need for high temporal resolution and accurate O monitoring. By taking advantage of the progress in artificial intelligence, deep learning models have been applied to satellite based...

Convolutional Neural Networks Facilitate Process Understanding of Megacity Ozone Temporal Variability.

Environmental science & technology
Ozone pollution is profoundly modulated by meteorological features such as temperature, air pressure, wind, and humidity. While many studies have developed empirical models to elucidate the effects of meteorology on ozone variability, they predominan...

High-spatial resolution ground-level ozone in Yunnan, China: A spatiotemporal estimation based on comparative analyses of machine learning models.

Environmental research
Monitoring ground-level ozone concentrations is a critical aspect of atmospheric environmental studies. Given the existing limitations of satellite data products, especially the lack of ground-level ozone characterization, and the discontinuity of gr...