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Estimating ground-level PM2.5 concentrations in Beijing using a satellite-based geographically and temporally weighted regression model

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TLDR
Wang et al. as discussed by the authors developed a geographically and temporally weighted regression (GTWR) model to account for spatial and temporal variability in the relationship between the non-continuous AQI-derived PM 2.5 and satellite-derived aerosol optical depth (AOD).
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This article is published in Remote Sensing of Environment.The article was published on 2017-09-01. It has received 156 citations till now. The article focuses on the topics: Unit-weighted regression & Linear regression.

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Emergency Admissions for Cardiovascular and Respiratory Diseases and the Chemical Composition of Fine Particle Air Pollution

TL;DR: In this paper, the authors investigated the association between hospital admission for cardiovascular disease (CVD) and respiratory disease and the chemical components of PM2.5 in the United States.
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Satellite-based mapping of daily high-resolution ground PM 2.5 in China via space-time regression modeling

TL;DR: In this article, a space-time regression model that is an improved geographically and temporally weighted regression (GTWR) with an interior point algorithm (IPA)-based efficient mechanism for selecting optimal parameter values, was developed to estimate a large set of daily PM2.5 concentrations.
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Predicting monthly high-resolution PM2.5 concentrations with random forest model in the North China Plain.

TL;DR: Li et al. as mentioned in this paper developed a random forest model using the latest Multi-angle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD), meteorological parameters, land cover and ground PM2.5 measurements from 2013 to 2015.
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Understanding meteorological influences on PM 2.5 concentrations across China: a temporal and spatial perspective

TL;DR: Wang et al. as mentioned in this paper employed the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM2.5 concentrations in 188 monitoring cities across China.
References
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Journal ArticleDOI

Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution

TL;DR: Fine particulate and sulfur oxide--related pollution were associated with all-cause, lung cancer, and cardiopulmonary mortality and long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopULmonary and lung cancer mortality.
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Fine Particulate Air Pollution and Hospital Admission for Cardiovascular and Respiratory Diseases

TL;DR: Short-term exposure to PM2.5 increases the risk for hospital admission for cardiovascular and respiratory diseases and was higher in counties located in the Eastern region of the United States, which included the Northeast, the Southeast, the Midwest, and the South.
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The Collection 6 MODIS aerosol products over land and ocean

TL;DR: The Collection 6 (C6) algorithm as mentioned in this paper was proposed to retrieve aerosol optical depth (AOD) and aerosol size parameters from MODIS-observed spectral reflectance.
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Global Estimates of Ambient Fine Particulate Matter Concentrations from Satellite-Based Aerosol Optical Depth: Development and Application

TL;DR: Satellite-derived total-column AOD, when combined with a chemical transport model, provides estimates of global long-term average PM2.5 concentrations, with significant spatial agreement with ground-based in situ measurements.
Journal ArticleDOI

Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies

TL;DR: Wang et al. as mentioned in this paper explored the relationship between column aerosol optical thickness (AOT) derived from the Moderate Resolution Imaging SpectroRadiometer (MODIS) on the Terra/Aqua satellites and hourly fine particulate mass (PM2.5) measured at the surface at seven locations in Jefferson county, Alabama for 2002.
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