[HTML][HTML] A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective …
X Ma, B Zou, J Deng, J Gao, I Longley, S Xiao… - Environment …, 2024 - Elsevier
Land use regression (LUR) models are widely used in epidemiological and environmental
studies to estimate humans' exposure to air pollution within urban areas. However, the early …
studies to estimate humans' exposure to air pollution within urban areas. However, the early …
[HTML][HTML] A novel ensemble-based statistical approach to estimate daily wildfire-specific PM2. 5 in California (2006–2020)
Though fine particulate matter (PM 2.5) has decreased in the United States (US) in the past
two decades, the increasing frequency, duration, and severity of wildfires significantly …
two decades, the increasing frequency, duration, and severity of wildfires significantly …
[HTML][HTML] Ensemble-based deep learning for estimating PM2. 5 over California with multisource big data including wildfire smoke
L Li, M Girguis, F Lurmann, N Pavlovic… - Environment …, 2020 - Elsevier
Introduction Estimating PM 2.5 concentrations and their prediction uncertainties at a high
spatiotemporal resolution is important for air pollution health effect studies. This is …
spatiotemporal resolution is important for air pollution health effect studies. This is …
Using street view imagery to predict street-level particulate air pollution
Land-use regression (LUR) models are frequently applied to estimate spatial patterns of air
pollution. Traditional LUR often relies on fixed-site measurements and GIS-derived variables …
pollution. Traditional LUR often relies on fixed-site measurements and GIS-derived variables …
Application of complete ensemble empirical mode decomposition based multi-stream informer (CEEMD-MsI) in PM2. 5 concentration long-term prediction
Nowadays, air pollution has become one of the most serious environmental problems facing
humanity and an inescapable obstacle limiting the sustainable development of cities and …
humanity and an inescapable obstacle limiting the sustainable development of cities and …
Application of nonlinear land use regression models for ambient air pollutants and air quality index
L Zhang, X Tian, Y Zhao, L Liu, Z Li, L Tao… - Atmospheric Pollution …, 2021 - Elsevier
Air pollution is a major global environmental problem that affects health. In view of this, it is
important to improve the prediction method of air pollutant concentrations to obtain accurate …
important to improve the prediction method of air pollutant concentrations to obtain accurate …
An interpretable self-adaptive deep neural network for estimating daily spatially-continuous PM2. 5 concentrations across China
Accurate estimation of daily spatially-continuous PM 2.5 (fine particulate matter)
concentration is a prerequisite to address environmental public health issues, and satellite …
concentration is a prerequisite to address environmental public health issues, and satellite …
Daily PM2.5 concentration estimates by county, ZIP code, and census tract in 11 western states 2008–2018
CE Reid, EM Considine, MM Maestas, G Li - Scientific data, 2021 - nature.com
We created daily concentration estimates for fine particulate matter (PM2. 5) at the centroids
of each county, ZIP code, and census tract across the western US, from 2008–2018. These …
of each county, ZIP code, and census tract across the western US, from 2008–2018. These …
Imputing environmental impact missing data of the industrial sector for Chinese cities: A machine learning approach
Data are the lifeblood of evidence-based decision-making and the raw material for
accountability. Collecting data to regularly evaluate industrial consumption and pollution at …
accountability. Collecting data to regularly evaluate industrial consumption and pollution at …
Satellite data for environmental justice: a scoping review of the literature in the United States
TK Sayyed, U Ovienmhada, M Kashani… - Environmental …, 2024 - iopscience.iop.org
In support of the environmental justice (EJ) movement, researchers, activists, and
policymakers often use environmental data to document evidence of the unequal distribution …
policymakers often use environmental data to document evidence of the unequal distribution …