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Air Pollutants

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Prediction of air pollutant concentration based on sparse response back-propagation training feedforward neural networks.

Environmental science and pollution research international
In this paper, we predict air pollutant concentration using a feedforward artificial neural network inspired by the mechanism of the human brain as a useful alternative to traditional statistical modeling techniques. The neural network is trained bas...

Artificial neural network models for prediction of daily fine particulate matter concentrations in Algiers.

Environmental science and pollution research international
Neural network (NN) models were evaluated for the prediction of suspended particulates with aerodynamic diameter less than 10-μm (PM10) concentrations. The model evaluation work considered the sequential hourly concentration time series of PM10, whic...

Modelling the removal of volatile pollutants under transient conditions in a two-stage bioreactor using artificial neural networks.

Journal of hazardous materials
A two-stage biological waste gas treatment system consisting of a first stage biotrickling filter (BTF) and second stage biofilter (BF) was tested for the removal of a gas-phase methanol (M), hydrogen sulphide (HS) and α-pinene (P) mixture. The biore...

Estimation of NMVOC emissions using artificial neural networks and economical and sustainability indicators as inputs.

Environmental science and pollution research international
This paper describes the development of an artificial neural network (ANN) model based on economical and sustainability indicators for the prediction of annual non-methane volatile organic compounds (NMVOCs) emissions in China for the period 2005-201...

A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach.

Environmental research
Existing evidence suggests that ambient ultrafine particles (UFPs) (<0.1µm) may contribute to acute cardiorespiratory morbidity. However, few studies have examined the long-term health effects of these pollutants owing in part to a need for exposure ...

Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models.

Journal of environmental management
Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, insufficient funds for monitoring and abatement programs, and political and social challenges in defin...

Characterizing air quality data from complex network perspective.

Environmental science and pollution research international
Air quality depends mainly on changes in emission of pollutants and their precursors. Understanding its characteristics is the key to predicting and controlling air quality. In this study, complex networks were built to analyze topological characteri...

Forecasting PM10 in Algiers: efficacy of multilayer perceptron networks.

Environmental science and pollution research international
Air quality forecasting system has acquired high importance in atmospheric pollution due to its negative impacts on the environment and human health. The artificial neural network is one of the most common soft computing methods that can be pragmatic...

Modeling of ammonia emission in the USA and EU countries using an artificial neural network approach.

Environmental science and pollution research international
Ammonia emissions at the national level are frequently estimated by applying the emission inventory approach, which includes the use of emission factors, which are difficult and expensive to determine. Emission factors are therefore the subject of es...

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...