Machine learning in environmental research: common pitfalls and best practices
Machine learning (ML) is increasingly used in environmental research to process large data
sets and decipher complex relationships between system variables. However, due to the …
sets and decipher complex relationships between system variables. However, due to the …
A review on emerging artificial intelligence (AI) techniques for air pollution forecasting: Fundamentals, application and performance
Accurate air quality forecasting is critical for systematic pollution control as well as public
health and wellness. Most of the traditional forecasting techniques have shown inconsistent …
health and wellness. Most of the traditional forecasting techniques have shown inconsistent …
[HTML][HTML] Mortality and morbidity effects of long-term exposure to low-level PM2. 5, BC, NO2, and O3: an analysis of European cohorts in the ELAPSE Project
BACKGROUND The growing scientific evidence for effects of air pollution on health at
concentrations below current air quality standards and the large burden of disease attributed …
concentrations below current air quality standards and the large burden of disease attributed …
Remote sensing of fluorescent humification levels and its potential environmental linkages in lakes across China
The pollution or eutrophication affected by dissolved organic matter (DOM) composition and
sources of inland waters had attracted concerns from the public and government in China …
sources of inland waters had attracted concerns from the public and government in China …
Monitoring water quality using proximal remote sensing technology
X Sun, Y Zhang, K Shi, Y Zhang, N Li, W Wang… - Science of the Total …, 2022 - Elsevier
Accurate, high spatial and temporal resolution water quality monitoring in inland waters is
vital for environmental management. However, water quality monitoring in inland waters by …
vital for environmental management. However, water quality monitoring in inland waters by …
Estimation of surface-level NO2 and O3 concentrations using TROPOMI data and machine learning over East Asia
Abstract In East Asia, air quality has been recognized as an important public health problem.
In particular, the surface concentrations of air pollutants are closely related to human life …
In particular, the surface concentrations of air pollutants are closely related to human life …
[HTML][HTML] Comparison of Machine Learning and Land Use Regression for fine scale spatiotemporal estimation of ambient air pollution: Modeling ozone concentrations …
Abstract Background Spatial linear Land-Use Regression (LUR) is commonly used for long-
term modeling of air pollution in support of exposure and epidemiological assessments …
term modeling of air pollution in support of exposure and epidemiological assessments …
Using a land use regression model with machine learning to estimate ground level PM2. 5
Ambient fine particulate matter (PM 2.5) has been ranked as the sixth leading risk factor
globally for death and disability. Modelling methods based on having access to a limited …
globally for death and disability. Modelling methods based on having access to a limited …
Evaluation of gap-filling approaches in satellite-based daily PM2. 5 prediction models
Approximately half of satellite aerosol retrievals are missing that limits the application of
satellite data in PM 2.5 pollution monitoring. To obtain spatiotemporally continuous PM 2.5 …
satellite data in PM 2.5 pollution monitoring. To obtain spatiotemporally continuous PM 2.5 …
[HTML][HTML] Long-term air pollution exposure and Parkinson's disease mortality in a large pooled European cohort: An ELAPSE study
Background The link between exposure to ambient air pollution and mortality from
cardiorespiratory diseases is well established, while evidence on neurodegenerative …
cardiorespiratory diseases is well established, while evidence on neurodegenerative …