Deep learning for air pollutant concentration prediction: A review
Air pollution has become one of the critical environmental problem in the 21st century and
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
[HTML][HTML] A systematic review of data mining and machine learning for air pollution epidemiology
C Bellinger, MS Mohomed Jabbar, O Zaïane… - BMC public health, 2017 - Springer
Background Data measuring airborne pollutants, public health and environmental factors
are increasingly being stored and merged. These big datasets offer great potential, but also …
are increasingly being stored and merged. These big datasets offer great potential, but also …
[HTML][HTML] Nitrogen Dioxide (NO2) Pollution Monitoring with Sentinel-5P Satellite Imagery over Europe during the Coronavirus Pandemic Outbreak
Nitrogen dioxide (NO2) is one of the main air quality pollutants of concern in many urban
and industrial areas worldwide, and particularly in the European region, where in 2017 …
and industrial areas worldwide, and particularly in the European region, where in 2017 …
[HTML][HTML] A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen …
J Chen, K de Hoogh, J Gulliver, B Hoffmann… - Environment …, 2019 - Elsevier
Empirical spatial air pollution models have been applied extensively to assess exposure in
epidemiological studies with increasingly sophisticated and complex statistical algorithms …
epidemiological studies with increasingly sophisticated and complex statistical algorithms …
Assessing PM2.5 Exposures with High Spatiotemporal Resolution across the Continental United States
A number of models have been developed to estimate PM2. 5 exposure, including satellite-
based aerosol optical depth (AOD) models, land-use regression, or chemical transport …
based aerosol optical depth (AOD) models, land-use regression, or chemical transport …
[HTML][HTML] Machine learning approaches for outdoor air quality modelling: A systematic review
Y Rybarczyk, R Zalakeviciute - Applied Sciences, 2018 - mdpi.com
Current studies show that traditional deterministic models tend to struggle to capture the non-
linear relationship between the concentration of air pollutants and their sources of emission …
linear relationship between the concentration of air pollutants and their sources of emission …
[HTML][HTML] Human health risk assessment for contaminated sites: A retrospective review
Soil contamination is a serious global hazard as contaminants can migrate to the human
body through the soil, water, air, and food, threatening human health. Human Health Risk …
body through the soil, water, air, and food, threatening human health. Human Health Risk …
A new hybrid spatio-temporal model for estimating daily multi-year PM2. 5 concentrations across northeastern USA using high resolution aerosol optical depth data
The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter
(PM 2.5) for epidemiology studies has increased substantially over the past few years …
(PM 2.5) for epidemiology studies has increased substantially over the past few years …
[HTML][HTML] A review of urban air pollution monitoring and exposure assessment methods
The impact of urban air pollution on the environments and human health has drawn
increasing concerns from researchers, policymakers and citizens. To reduce the negative …
increasing concerns from researchers, policymakers and citizens. To reduce the negative …
Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches
Exposure assessment for elemental components of particulate matter (PM) using land use
modeling is a complex problem due to the high spatial and temporal variations in pollutant …
modeling is a complex problem due to the high spatial and temporal variations in pollutant …