AIMC Topic: Air Pollution

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Particle number emissions on mountainous roads: machine learning insights from on-road testing.

Environmental research
Mountainous roads pose unique challenges for controlling vehicular fine particulate number (PN) emissions, a critical pollutant impacting air quality and public health. This study integrates on-road testing with interpretable machine learning to anal...

Regional PM2.5 pollution forecasting using a hybrid model based on multi-scales feature fusion and deep learning algorithms.

PloS one
The issue of regional haze pollution has become increasingly prominent. However, early warning models for regional haze pollution are significantly lacking. To accurately predict regional PM2.5 pollution, hourly average concentration data of pollutan...

Machine learning-based forecasting of air quality index under long-term environmental patterns: A comparative approach with XGBoost, LightGBM, and SVM.

PloS one
Air pollution is a global problem that threatens environmental sustainability and severely affects public health. Monitoring air quality and predicting future pollution levels are critical for creating effective environmental policies and enabling in...

Advancing Air Pollution Exposure Models with Open-Vocabulary Object Detection and Semantic Segmentation of Street-View Images.

Environmental science & technology
Mobile monitoring campaigns combined with land use regression (LUR) models effectively capture fine-scale spatial variations in urban air pollution. However, traditional predictor variables often fail to capture the nuances of the built environment a...

A Novel Framework for Airshed Delineation and PM Estimation across India Using Machine Learning and Spatial Clustering.

Environmental science & technology
Air pollution continues to pose a major challenge in India, with PM being a key contributor to serious health risks. Its spatial distribution is influenced by climatic, topographic, and anthropogenic factors, which are often poorly represented in ana...

Comparative evaluation of machine learning algorithms for greenhouse gas emission forecasting: a case study of Turkey (2012-2021).

Environmental monitoring and assessment
Accurate forecasting of greenhouse gas (GHG) emissions is essential for assessing climate change dynamics and developing evidence-based environmental policies. This study aims to comparatively evaluate the prediction performance of various machine le...

Refining Air Pollution Exposure Estimates: A Comparison of Citywide and Neighborhood Land Use Regression Models in Toronto.

Environmental science & technology
Land use regression (LUR) models assess air pollution exposure but often struggle with transferability (predicting concentrations in areas without measurements) and generalizability (capturing spatial patterns across neighborhoods). This study evalua...

Analysis of spatiotemporal variation characteristics of atmospheric quality in China's city clusters from 2015 to 2023 and their socio-economic driving forces.

Journal of environmental management
With the rapid economic development in China, air quality issues have emerged as major challenges to the country's sustainable development. This study utilizes ground monitoring data from 1248 monitoring Stations across China, constructs a kilometer ...

Machine learningdriven framework for realtime air quality assessment and predictive environmental health risk mapping.

Scientific reports
This research introduces a practical and innovative approach for real-time air quality assessment and health risk prediction, focusing on urban, industrial, suburban, rural, and traffic-heavy environments. The framework integrates data from multiple ...

Association between air pollution and type II diabetes in Italy from clinical data and population-weighted exposure at the municipality level.

Scientific reports
A growing body of literature supports the association between ambient particulate pollution and the risk of type 2 diabetes (T2DM). Both issues are particularly relevant in Italy. This study investigates the relationship between T2DM and exposure to ...