AIMC Topic: Nitrogen Oxides
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Accurate and efficient prediction of atmospheric PM, PM, PM, and O concentrations using a customized software package based on a machine-learning algorithm.
Chemosphere
Nov 16, 2024
Particulate matter (PM) and ozone (O) pollution have been attracting increasing attention recently due to their severe harm to human health. PM and O are secondary pollutants, and there remain significant challenges in accurately and efficiently pred...
3DVar sectoral emission inversion based on source apportionment and machine learning.
Environmental pollution (Barking, Essex : 1987)
Oct 18, 2024
Air quality models are increasingly important in air pollution forecasting and control. Sectoral emissions significantly impact the accuracy of air quality models and source apportionment. This paper studied the 3DVar (three-dimensional variational) ...
Long-term Evaluation of Machine Learning Based Methods for Air Emission Monitoring.
Environmental management
Sep 30, 2024
Machine learning (ML) techniques have been researched and used in various environmental monitoring applications. Few studies have reported the long-term evaluation of such applications. Discussions regarding the risks and regulatory frameworks of ML ...
Combining Google traffic map with deep learning model to predict street-level traffic-related air pollutants in a complex urban environment.
Environment international
Sep 6, 2024
BACKGROUND: Traffic-related air pollution (TRAP) is a major contributor to urban pollution and varies sharply at the street level, posing a challenge for air quality modeling. Traditional land use regression models combined with data from fixed monit...
Soft sensing of NOx emission from waste incineration process based on data de-noising and bidirectional long short-term memory neural networks.
Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Jul 30, 2024
Continuous emission monitoring system is commonly employed to monitor NOx emissions in municipal solid waste incineration (MSWI) processes. However, it still encounters the challenges of regular maintenance and measurement lag. These issues significa...
Identifying Driving Factors of Atmospheric NO with Machine Learning.
Environmental science & technology
Jun 18, 2024
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 ...
Cluster-based bagging of constrained mixed-effects models for high spatiotemporal resolution nitrogen oxides prediction over large regions.
Environment international
May 8, 2019
BACKGROUND: Accurate estimation of nitrogen dioxide (NO) and nitrogen oxide (NO) concentrations at high spatiotemporal resolutions is crucial for improving evaluation of their health effects, particularly with respect to short-term exposures and acut...
Space-time trends of PM constituents in the conterminous United States estimated by a machine learning approach, 2005-2015.
Environment international
Nov 7, 2018
Particulate matter with aerodynamic diameter less than 2.5 μm (PM) is a complex mixture of chemical constituents emitted from various emission sources or through secondary reactions/processes; however, PM is regulated mostly based on its total mass c...
A fuzzy logic urea dosage controller design for two-cell selective catalytic reduction systems.
ISA transactions
Dec 23, 2017
Diesel engines have dominated in the heavy-duty vehicular and marine power source. However, the induced air pollution is a big problem. As people's awareness of environmental protection increasing, the emission regulations of diesel-engine are becomi...
Prediction and quantifying parameter importance in simultaneous anaerobic sulfide and nitrate removal process using artificial neural network.
Environmental science and pollution research international
Dec 20, 2014
The present investigation deals with the prediction of the performance of simultaneous anaerobic sulfide and nitrate removal in an upflow anaerobic sludge bed (UASB) reactor through an artificial neural network (ANN). Influent sulfide concentration, ...
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