AIMC Topic: Air Pollution

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Evaluating the transferability of low-cost sensor calibration using ANFIS: a field study in Putrajaya, Malaysia.

Environmental monitoring and assessment
This study evaluates the robustness of a previously developed calibration model for low-cost ozone sensors, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS). The model was deployed at a different site without retraining. It was tested in Pu...

Optimization of spatio-temporal ozone (O) pollution modeling using an ensemble machine model learning with a swarm-based metaheuristic algorithm.

Ecotoxicology and environmental safety
The future of ozone (O) pollution presents significant environmental and public health challenges worldwide. High O levels can harm respiratory health, exacerbating conditions such as asthma and increasing the risk of cardiovascular diseases. Address...

Assessing 3-D variability of ultrafine particle using a Geo-AI modelling approach: A case study in Zhunan-Miaoli, Taiwan.

Environmental pollution (Barking, Essex : 1987)
Previous air pollution modeling studies have predominantly emphasized horizontal distributions, overlooking the critical vertical variability of pollutant concentrations in urban environments. Therefore, the three-dimensional (3-D) behavior of air po...

Analysis of interactions of particle-associated oxidative potential sources using multilayer perceptron neural networks: A case study in Shenyang, China.

Environmental pollution (Barking, Essex : 1987)
The oxidative potential (OP) of particulate matter (PM) is a possible indicator for assessing the oxidative-imbalance risk caused by PM exposure. The OP contributions of different PM sources exhibit nonlinear relationships, and the specific patterns ...

Artificial intelligence platform to predict children's hospital care for respiratory disease using clinical, pollution, and climatic factors.

Journal of global health
BACKGROUND: Hospitals and health care systems may benefit from artificial intelligence (AI) and big data to analyse clinical information combined with external sources. Machine learning, a subset of AI, uses algorithms trained on data to generate pre...

Racial and ethnic disparities in exposure to short-term NO air pollution in California during 1980-2022.

Journal of hazardous materials
Historical racial and ethnic disparities in short-term exposure to ambient nitrogen dioxide (NO) have rarely been investigated, primarily due to the lack of spatiotemporally resolved NO data covering the historical period. In this study, we used publ...

Using open data to derive parsimonious data-driven models for uncovering the influence of local traffic and meteorology on air quality: The case of Madrid.

Environmental pollution (Barking, Essex : 1987)
Air pollution remains a critical public health and environmental challenge, particularly in urban areas where traffic emissions and meteorological conditions strongly influence air quality. While Machine Learning (ML) techniques have been increasingl...

Predictive modelling of air pollution affecting human tuberculosis risk on Mainland China.

Scientific reports
In this study, we investigated the correlation between air pollution indicators and pulmonary tuberculosis (TB) incidence and mortality rates across provincial administrative regions of China from January 2013 to December 2020 to develop predictive m...

Fusing satellite imagery and ground-based observations for PM air pollution modeling in Iran using a deep learning approach.

Scientific reports
With the rapid advancement of urbanization and industrialization in cities, air pollution has become one of the significant environmental challenges and issues in many countries. The concentration of particulate matter with an aerodynamic diameter of...

Air Pollution and Autism Spectrum Disorder: Unveiling Multipollutant Risks and Sociodemographic Influences in California.

Environmental health perspectives
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevalence worldwide. Air pollution may be a major contributor to the rise in ASD cases. This study investigated how the risk of ASD associated with prenatal...