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Air Pollutants

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Explainable deep learning predictions for illness risk of mental disorders in Nanjing, China.

Environmental research
Epidemiological studies have revealed the associations of air pollutants and meteorological factors with a range of mental health conditions. However, little is known about local explanations and global understanding on the importance and effect of i...

Surveillance of ship emissions and fuel sulfur content based on imaging detection and multi-task deep learning.

Environmental pollution (Barking, Essex : 1987)
Shipping makes up the major proportion of global transportation and results in an increasing emission of air pollutants. It accounts for 3.1%, 13%, and 15% of the annual global emissions of CO, SO, and NO, respectively. Hence, effective regulatory me...

Associations between trees and grass presence with childhood asthma prevalence using deep learning image segmentation and a novel green view index.

Environmental pollution (Barking, Essex : 1987)
Limitations of Normalized Difference Vegetation Index (NDVI) potentially contributed to the inconsistent findings of greenspace exposure and childhood asthma. The aim of this study was to use a novel greenness exposure assessment method, capable of o...

Volumetric monitoring of airborne particulate matter concentration using smartphone-based digital holographic microscopy and deep learning.

Journal of hazardous materials
Airborne particulate matter (PM) has become a global environmental issue. This PM has harmful effects on public health and precision industries. Conventional air-quality monitoring methods usually utilize expensive equipment, and they are cumbersome ...

Understanding global changes in fine-mode aerosols during 2008-2017 using statistical methods and deep learning approach.

Environment international
Despite their extremely small size, fine-mode aerosols have significant impacts on the environment, climate, and human health. However, current understandings of global changes in fine-mode aerosols are limited. In this study, we employed newly devel...

Asthma-prone areas modeling using a machine learning model.

Scientific reports
Nowadays, owing to population growth, increasing environmental pollution, and lifestyle changes, the number of asthmatics has significantly increased. Therefore, the purpose of our study was to determine the asthma-prone areas in Tehran, Iran conside...

Experimental investigation and optimal combustion control of untreated landfill gas via fuzzy logic rule knowledge based approach.

Waste management (New York, N.Y.)
Optimal combustion control of untreated landfill gas is proposed for an effective usage and a low-cost solution in waste to energy technologies. Variations of methane concentration in untreated landfill gas over time cause undesired performance of co...

Novel Method Based on Hollow Laser Trapping-LIBS-Machine Learning for Simultaneous Quantitative Analysis of Multiple Metal Elements in a Single Microsized Particle in Air.

Analytical chemistry
Elemental identification of individual microsized aerosol particles is an important topic in air pollution studies. However, simultaneous and quantitative analysis of multiple constituents in a single aerosol particle with the noncontact in situ mann...

PM2.5 concentration modeling and prediction by using temperature-based deep belief network.

Neural networks : the official journal of the International Neural Network Society
Air quality prediction is a global hot issue, and PM is an important factor affecting air quality. Due to complicated causes of formation, PM prediction is a thorny and challenging task. In this paper, a novel deep learning model named temperature-ba...

Combining citizen science and deep learning for large-scale estimation of outdoor nitrogen dioxide concentrations.

Environmental research
Reliable estimates of outdoor air pollution concentrations are needed to support global actions to improve public health. We developed a new approach to estimating annual average outdoor nitrogen dioxide (NO) concentrations using approximately 20,000...