AIMC Topic: Air Pollutants

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Machine Learning-Assisted Prediction and Exploration of the Homogeneous Oxidation of Mercury in Coal Combustion Flue Gas.

Environmental science & technology
Mercury emission from coal combustion flue gas is a significant environmental concern due to its detrimental effects on ecosystems and human health. Elemental mercury (Hg) is the dominant species in flue gas and is hard to immobilize. Therefore, it i...

Research on the influencing factors of PM in China at different spatial scales based on machine learning algorithm.

Environment international
PM pollution is one of the prominent environmental issues currently faced in China, influenced by various factors and showed significant spatial differences. In this study, the Light Gradient Boosting Machine (LightGBM) model was employed in combinat...

Exploring the link between grandmaternal air pollution exposure and Grandchild's ASD risk: A multigenerational population-based study in California.

Environment international
BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with increasing prevalence. While genetics play a strong causal role, among environmental factors, air pollution (AP) exposure in pregnancy and infancy has been strongly endo...

Improved surface NO Retrieval: Double-layer machine learning model construction and spatio-temporal characterization analysis in China (2018-2023).

Journal of environmental management
As an important atmospheric pollutant causing serious harm to human health and the natural environment, monitoring of surface NO (SNO) level is of critical importance. However, the current SNO retrieval models neglect to consider the influence of NO ...

Refining source-specific lung cancer risk assessment from PM-bound PAHs: Integrating component-based potency factors and machine learning in Ningbo, China.

Ecotoxicology and environmental safety
The component-based potency factor approach, combined with benzo[a]pyrene (BaP) unit risk values from the World Health Organization (WHO), is commonly used to assess lung excess cancer risk (LECR) from polycyclic aromatic hydrocarbons (PAHs). However...

Exploring multivariate machine learning frameworks to parallelize PM simultaneous estimations across the continental United States.

Environmental pollution (Barking, Essex : 1987)
Fine particulate matter (PM2.5) comprises diverse chemical components, including elemental carbon (EC), silicon (SI), sulfate (SO), and calcium (CA), each linked to varied health and environmental impacts. Accurately estimating these components' spat...

Advancing low-cost air quality monitor calibration with machine learning methods.

Environmental pollution (Barking, Essex : 1987)
Low-cost monitors for measuring airborne contaminants have gained popularity due to their affordability, portability, and ease of use. However, they often exhibit significant biases compared to high-cost reference instruments. For optimal accuracy, t...

Meteorological and traffic effects on air pollutants using Bayesian networks and deep learning.

Journal of environmental sciences (China)
Traffic emissions have become the major air pollution source in urban areas. Therefore, understanding the highly non-stational and complex impact of traffic factors on air quality is very important for building air quality prediction models. Using re...

Mapping Regional Meteorological Processes to Ozone Variability in the North China Plain and the Yangtze River Delta, China.

Environmental science & technology
High-concentration ozone threatens human health and ecosystems, modulated by dynamic, multiscale meteorological processes. Existing machine learning studies for ozone prediction rarely incorporate the spatiotemporal evolution of regional meteorologic...

Distribution characteristics of volatile organic compounds and its multidimensional impact on ozone formation in arid regions based on machine learning algorithms.

Environmental pollution (Barking, Essex : 1987)
Volatile Organic Compounds (VOCs) are key components of atmospheric pollution and play a critical role in ozone (O) formation. Understanding their distribution and pollution sources is essential to grasping the multifaceted impact of VOCs on O produc...