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Estimating Intra-Urban Inequities in PM
2.5
-Attributable Health Impacts: A Case Study for Washington, DC
Aaron van Donkelaar
,
Randall V. Martin
Atelier Future
Office of Research and Development
科研成果
:
期刊稿件
›
文章
›
同行评审
34
引用 （Scopus）
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探究 'Estimating Intra-Urban Inequities in PM
2.5
-Attributable Health Impacts: A Case Study for Washington, DC' 的科研主题。它们共同构成独一无二的指纹。
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Keyphrases
Intra-urban
100%
Health Impact
100%
Health Risk
100%
Particulate Matter 2.5 (PM2.5)
100%
Washington DC
100%
Urban Inequity
100%
Disease Rate
75%
Air Pollution Exposure
50%
Inequity
50%
PM2.5 Concentration
50%
Pollution Level
50%
Population Subgroups
50%
Asthma Emergency Department Visits
50%
All-cause Mortality
25%
Pollution
25%
Ischemic Heart Disease
25%
Air Pollution
25%
Lung Cancer
25%
Recent Advances
25%
Chronic Obstructive Pulmonary Disease
25%
Attributable Cases
25%
Attributable Mortality
25%
High-resolution
25%
Annual Mean
25%
Population Estimate
25%
People of Color
25%
Low-income Households
25%
Satellite Products
25%
Fine Particulate Matter PM2.5
25%
Exposure Level
25%
Attributable Burden
25%
Educational Attainment
25%
Health Burden
25%
Spatially Resolved
25%
Surface PM2.5
25%
Rate Estimate
25%
Health Disparities
25%
Mean Surface
25%
Concentration Estimates
25%
Granular Data
25%
Health Impact Functions
25%
Air Pollution Levels
25%
Zip Code
25%
Cause-specific Death
25%
Satellite Remote Sensing Data
25%
Urban Heterogeneity
25%
Surface Pollution
25%
Urban Disparity
25%
Immunology and Microbiology
Surface Property
100%
Asthma
100%
All Cause Mortality
50%
Disease Burden
50%
Mental Capacity
50%
Particulate Matter
50%
Remote Sensing
50%
Health Disparity
50%
Medicine and Dentistry
Particular Matter 2.5
100%
Disease
57%
Health Hazard
57%
Asthma
28%
Emergency Department
28%
Ischemic Heart Disease
14%
All Cause Mortality
14%
Apoplexy
14%
Household
14%
Lung Cancer
14%
Chronic Obstructive Pulmonary Disease
14%
Fine Particulate Matter
14%
Mental Capacity
14%
Disease Burden
14%
Remote Sensing
14%
Health Disparity
14%
Earth and Planetary Sciences
Particular Matter 2.5
100%
Washington
100%
Air Pollution
57%
Household Income
14%
Fine Particulate Matter
14%
Educational Attainment
14%
Satellite Remote Sensing
14%
Mathematics
Population Subgroup
100%
Household Income
50%
Data Input
50%
Economics, Econometrics and Finance
Emergency Department
100%
Low Income Household
50%
Satellite Communication
50%