AIMC Topic: Particulate Matter
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3DVar sectoral emission inversion based on source apportionment and machine learning.
Environmental pollution (Barking, Essex : 1987)
Oct 18, 2024
Air quality models are increasingly important in air pollution forecasting and control. Sectoral emissions significantly impact the accuracy of air quality models and source apportionment. This paper studied the 3DVar (three-dimensional variational) ...
Enhancing indoor PM predictions based on land use and indoor environmental factors by applying machine learning and spatial modeling approaches.
Environmental pollution (Barking, Essex : 1987)
Oct 18, 2024
The presence of fine particulate matter (PM) indoors constitutes a significant component of overall PM exposure, as individuals spend 90% of their time indoors; however, personal monitoring for large cohorts is often impractical. In light of this, th...
Hourly PM concentration prediction for dry bulk port clusters considering spatiotemporal correlation: A novel deep learning blending ensemble model.
Journal of environmental management
Oct 1, 2024
Accurate prediction of PM concentrations in ports is crucial for authorities to combat ambient air pollution effectively and protect the health of port staff. However, in port clusters formed by multiple neighboring ports, we encountered several chal...
Does COVID-19 lockdown matter for air pollution in the short and long run in China? A machine learning approach to policy evaluation.
Journal of environmental management
Sep 24, 2024
This paper leverages a data-driven two-step approach to effectively evaluate the effects of COVID-19 lockdown on air pollution in both the short and long-term in China. Using air pollution, meteorological conditions, and air mass clusters from 34 air...
Ultralow-resistance and self-sterilization biodegradable nanofibrous membranes for efficient PM removal and machine learning-assisted health management.
Journal of hazardous materials
Sep 16, 2024
The development of multifunctional nanofibrous membranes (NFMs) that enable anti-viral protection during air purification and respiratory disease diagnosis for health management is of increasing importance. Herein, we unraveled a heterostructure-enha...
Performance analysis of machine learning models for AQI prediction in Gorakhpur City: a critical study.
Environmental monitoring and assessment
Sep 12, 2024
Air pollution and climate change are two complementary forces that directly or indirectly affect the environment's physical, chemical, and biological processes. The air quality index is a parameter defined to cope with this effect of air pollution. T...
Unveiling the potential of a novel portable air quality platform for assessment of fine and coarse particulate matter: in-field testing, calibration, and machine learning insights.
Environmental monitoring and assessment
Sep 4, 2024
Although low-cost air quality sensors facilitate the implementation of denser air quality monitoring networks, enabling a more realistic assessment of individual exposure to airborne pollutants, their sensitivity to multifaceted field conditions is o...
Daily PM2.5 concentration prediction based on variational modal decomposition and deep learning for multi-site temporal and spatial fusion of meteorological factors.
Environmental monitoring and assessment
Aug 29, 2024
Air pollution, particularly PM2.5, has long been a critical concern for the atmospheric environment. Accurately predicting daily PM2.5 concentrations is crucial for both environmental protection and public health. This study introduces a new hybrid m...
Elucidating and forecasting the organochlorine pesticides in suspended particulate matter by a two-stage decomposition based interpretable deep learning approach.
Water research
Aug 23, 2024
Accurately predicting the concentration of organochlorine pesticides (OCPs) presents a challenge due to their complex sources and environmental behaviors. In this study, we introduced a novel and advanced model that combined the power of three distin...
A new attention-based CNN_GRU model for spatial-temporal PM prediction.
Environmental science and pollution research international
Aug 23, 2024
Accurately predicting the spatial-temporal distribution of PM is challenging due to missing data and selecting an appropriate modeling method. Effective imputation of missing data must consider the relationships between variables while preserving the...
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