AIMC Topic: Air Pollutants

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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...

The potential of decision tree application in threshold analysis of hazardous volatile organic compound release from biochar: Implications for environmental risk assessment.

The Science of the total environment
The release of hazardous volatile organic compounds (HVOCs) from biochar poses a potential threat to both human health and the environment. This study investigates how low pyrolysis temperature (HTT) and the chemical characteristics of lignocellulosi...

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 ...

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...

Familial Differences in Personal PM Exposure within a Rural African Community Explained with Spatiotemporal Exposure Apportionment.

Environmental science & technology
Exposure to fine particulate matter (PM) from solid-fuel combustion is a major determinant of global morbidity and mortality. However, variations in exposure remain uncertain across many high-risk populations. This work describes personal PM exposure...

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...