AIMC Topic: Air Pollution
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Enhancing air quality predictions in Chile: Integrating ARIMA and Artificial Neural Network models for Quintero and Coyhaique cities.
PloS one
Jan 10, 2025
In this comprehensive analysis of Chile's air quality dynamics spanning 2016 to 2021, the utilization of data from the National Air Quality Information System (SINCA) and its network of monitoring stations was undertaken. Quintero, Puchuncaví, and Co...
Predictive modeling of air quality in the Tehran megacity via deep learning techniques.
Scientific reports
Jan 8, 2025
Air pollution is a significant challenge in metropolitan areas, where increasing amounts of air pollutants threaten public health and environmental safety. The present study aims to forecast the concentrations of various air pollutants, including CO,...
Forecasting O and NO concentrations with spatiotemporally continuous coverage in southeastern China using a Machine learning approach.
Environment international
Jan 2, 2025
Ozone (O) is a significant contributor to air pollution and the main constituent ofphotochemical smog that plagues China. Nitrogen dioxide (NO) is a significant air pollutant and a critical trace gas in the Earth's atmosphere. The presence of O and N...
Spatiotemporal analysis of airborne pollutants and health risks in Mashhad metropolis: enhanced insights through sensitivity analysis and machine learning.
Environmental geochemistry and health
Dec 26, 2024
The study delved into an extensive assessment of outdoor air pollutant levels, focusing specifically on PM, SO, NO, and CO, across the Mashhad metropolis from 2017 to 2021. In tandem, it explored their intricate correlations with meteorological condi...
Achieving pollution abatement and carbon reduction synergistically: How can industrial robots play a role?
Journal of environmental management
Dec 24, 2024
Intelligent manufacturing and green development are pivotal issues in China's pursuit of high-quality economic growth. As the core carrier of artificial intelligence-driven production transformations, industrial robots' role in synergizing enterprise...
Mapping of high-resolution daily particulate matter (PM) concentration at the city level through a machine learning-based downscaling approach.
Environmental monitoring and assessment
Dec 23, 2024
PM pollution is a major global concern, especially in Vietnam, due to its harmful effects on health and the environment. Monitoring local PM levels is crucial for assessing air quality. However, Vietnam's state-of-the-art (SOTA) dataset with a 3 km r...
Machine learning helps reveal key factors affecting tire wear particulate matter emissions.
Environment international
Dec 19, 2024
Tire wear particles (TWPs) are generated with every rotation of the tire. However, obtaining TWPs under real driving conditions and revealing key factors affecting TWPs are challenging. In this study, we obtained a TWPs dataset by simulating tire wea...
Spatiotemporal modeling of long-term PM concentrations and population exposure in Greece, using machine learning and statistical methods.
The Science of the total environment
Dec 18, 2024
The lack of high-resolution, long-term PM observations in Greece and the Eastern Mediterranean hampers the development of spatial models that are crucial for providing representative exposure estimates to health studies. This work presents a spatial ...
Improving WRF-Chem PM predictions by combining data assimilation and deep-learning-based bias correction.
Environment international
Dec 15, 2024
In numerical model simulations, data assimilation (DA) on the initial conditions and bias correction (BC) of model outputs have been proven to be promising approaches to improving PM (particulate matter with an aerodynamic equivalent diameter of ≤ 2....
Forecasting air pollution with deep learning with a focus on impact of urban traffic on PM10 and noise pollution.
PloS one
Dec 10, 2024
Air pollution constitutes a significant worldwide environmental challenge, presenting threats to both our well-being and the purity of our food supply. This study suggests employing Recurrent Neural Network (RNN) models featuring Long Short-Term Memo...
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