Creating National Air Pollution Models for Population Exposure Assessment in Canada
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Summary
Applying national models to routinely collected population location data can extend land use modeling techniques to population exposure assessment and to informing surveillance, policy, and regulation.
- Type
- article
- Published
- 2011-03-31
- Cited by
- 262
- References
- 51
- Access
- Open access
- OpenAlex
- https://openalex.org/W1963738994
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:5634323
Keywords
Environmental science, Population, Air pollution, Pollutant, Atmospheric sciences
References
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Cited by
- Assessment and statistical modeling of the relationship between remotely sensed aerosol optical depth and PM2.5 in the eastern United States.
- Assessment of the magnitude and recent trends in satellite-derived ground-level nitrogen dioxide over North America
- A national satellite-based land-use regression model for air pollution exposure assessment in Australia.
- A Hybrid Approach to Estimating National Scale Spatiotemporal Variability of PM2.5 in the Contiguous United States
- Assessment of Particulate Matter Levels in Vulnerable Communities in North Charleston, South Carolina prior to Port Expansion
- Exposure to traffic-related air pollution and the risk of developing breast cancer among women in eight Canadian provinces: a case-control study.
- Gene Expression Analysis of PCB Exposed Children: Understanding Toxicity and Disease Process
- Use of generalized additive models and cokriging of spatial residuals to improve land-use regression estimates of nitrogen oxides in Southern California
- The moving-window Bayesian Maximum Entropy framework: Estimation of PM2.5 yearly average concentration across the contiguous United States
- Toward the next generation of air quality monitoring: Particulate Matter
- Estimating the global abundance of ground level presence of particulate matter (PM2.5)
- Large-scale Bayesian spatial modelling of air pollution for policy support
- Performance of Multi-City Land Use Regression Models for Nitrogen Dioxide and Fine Particles
- Application of the deletion/substitution/addition algorithm to selecting land use regression models for interpolating air pollution measurements in California
- Comparison of Remote Sensing and Fixed-Site Monitoring Approaches for Examining Air Pollution and Health in a National Study Population
- Remote sensing of exposure to NO2: Satellite versus ground-based measurement in a large urban area
- Satellite NO2 data improve national land use regression models for ambient NO2 in a small densely populated country
- Assessing environmental inequalities in ambient air pollution across urban Australia.
- A regionalized national universal kriging model using Partial Least Squares regression for estimating annual PM2.5 concentrations in epidemiology
- A Bayesian hierarchical model for assessing the impact of human activity on nitrogen dioxide concentrations in Europe
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