AI Medical Compendium Journal:
Environment international

Showing 41 to 50 of 55 articles

Estimate ecotoxicity characterization factors for chemicals in life cycle assessment using machine learning models.

Environment international
In life cycle assessment, characterization factors are used to convert the amount of the chemicals and other pollutants generated in a product's life cycle to the standard unit of an impact category, such as ecotoxicity. However, as a widely used imp...

Environmental odour management by artificial neural network - A review.

Environment international
Unwanted odour emissions are considered air pollutants that may cause detrimental impacts to the environment as well as an indicator of unhealthy air to the affected individuals resulting in annoyance and health related issues. These pollutants are c...

Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul, South Korea.

Environment international
Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land use regression (LUR) models. Mobile sampling campaigns deploying low-cost (<$300) air quality sensors could potentially offer an inexpensive and practic...

A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide.

Environment international
Empirical spatial air pollution models have been applied extensively to assess exposure in epidemiological studies with increasingly sophisticated and complex statistical algorithms beyond ordinary linear regression. However, different algorithms hav...

Cluster-based bagging of constrained mixed-effects models for high spatiotemporal resolution nitrogen oxides prediction over large regions.

Environment international
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...

Metabarcoding and machine learning analysis of environmental DNA in ballast water arriving to hub ports.

Environment international
While ballast water has long been linked to the global transport of invasive species, little is known about its microbiome. Herein, we used 16S rRNA gene sequencing and metabarcoding to perform the most comprehensive microbiological survey of ballast...

Spatiotemporal continuous estimates of PM concentrations in China, 2000-2016: A machine learning method with inputs from satellites, chemical transport model, and ground observations.

Environment international
Ambient exposure to fine particulate matter (PM) is known to harm public health in China. Satellite remote sensing measurements of aerosol optical depth (AOD) were statistically associated with in-situ observations after 2013 to predict PM concentrat...

Space-time trends of PM constituents in the conterminous United States estimated by a machine learning approach, 2005-2015.

Environment international
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...

Urinary concentrations and profiles of organophosphate and pyrethroid pesticide metabolites and phenoxyacid herbicides in populations in eight countries.

Environment international
Concentrations of nine metabolites of organophosphate and pyrethroid insecticides, as well as two phenoxy herbicides, were determined in 322 urine samples collected from eight countries during 2006-2014 by high-performance liquid chromatography-tande...