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Air Pollution

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Prediction of pollutant emission characteristics in ISO50001 energy management in the Americas: Uni and multivariate machine learning approach.

The Science of the total environment
The American continent is experiencing significant economic and industrial development driven by sustainability principles. In this context, discussions on improving energy consumption have become increasingly frequent and dynamic across various sect...

Quantifying the multiple environmental, health, and economic co-benefits from the adoption of carbon capture technology in the power sector in southern Iraq, using a recurrent neural network-based health assessment approach.

Journal of environmental management
This study introduces a novel integrated quantitative modeling framework to assess the multiple environmental, health, and economic benefits from implementing carbon capture technology in the power sector of Basra province, Iraq. This province is str...

Accurately Predicting Spatiotemporal Variations of Near-Surface Nitrous Acid (HONO) Based on a Deep Learning Approach.

Environmental science & technology
Gaseous nitrous acid (HONO) is identified as a critical precursor of hydroxyl radicals (OH), influencing atmospheric oxidation capacity and the formation of secondary pollutants. However, large uncertainties persist regarding its formation and elimin...

Factors of acute respiratory infection among under-five children across sub-Saharan African countries using machine learning approaches.

Scientific reports
Symptoms of Acute Respiratory infections (ARIs) among under-five children are a global health challenge. We aimed to train and evaluate ten machine learning (ML) classification approaches in predicting symptoms of ARIs reported by mothers among child...

Quantifying the pollution changes and meteorological dependence of airborne trace elements coupling source apportionment and machine learning.

The Science of the total environment
Airborne trace elements (TEs) present in atmospheric fine particulate matter (PM) exert notable threats to human health and ecosystems. To explore the impact of meteorological conditions on shaping the pollution characteristics of TEs and the associa...

Innovative approaches for accurate ozone prediction and health risk analysis in South Korea: The combined effectiveness of deep learning and AirQ.

The Science of the total environment
Short-term exposure to ground-level ozone (O) poses significant health risks, particularly respiratory and cardiovascular diseases, and mortality. This study addresses the pressing need for accurate O forecasting to mitigate these risks, focusing on ...

Machine-learning-based corrections of CMIP6 historical surface ozone in China during 1950-2014.

Environmental pollution (Barking, Essex : 1987)
Due to a lack of long-term observations in China, reports on historical ozone concentration are severely limited. In this study, by combining observation, reanalysis and model simulation data, XGBoost machine learning algorithm is used to correct the...

Predicting PM2.5 concentration with enhanced state-trend awareness and uncertainty analysis using bagging and LSTM neural networks.

Journal of environmental quality
Monitoring air pollutants, particularly PM2.5, which refers to fine particulate matter with a diameter of 2.5 µm or smaller, has become a focal point of environmental protection efforts worldwide. This study introduces the concept of state-trend awar...

Identifying Driving Factors of Atmospheric NO with Machine Learning.

Environmental science & technology
Dinitrogen pentoxide (NO) plays an essential role in tropospheric chemistry, serving as a nocturnal reservoir of reactive nitrogen and significantly promoting nitrate formations. However, identifying key environmental drivers of NO formation remains ...

IoT-based monitoring system and air quality prediction using machine learning for a healthy environment in Cameroon.

Environmental monitoring and assessment
This paper is aimed at developing an air quality monitoring system using machine learning (ML), Internet of Things (IoT), and other elements to predict the level of particulate matter and gases in the air based on the air quality index (AQI). It is a...