About the Project
The aim of this project is to investigate the relative performance of two very different modelling approaches used to estimate spatially resolved pollution concentrations for use in epidemiological studies exploring the health effects of long-term exposures to air pollutants. Specifically the objectives will be: To quantify and compare the bias in the estimation of individual exposure (based on residential addresses) for use in epidemiological studies of effects of long-term exposures attributable to exposure estimation measurement error inherent in various air pollution modeling approaches. To evaluate the need of finer spatial resolution in the air pollution model output (residence vs grid of certain area) given the presence of other errors (e.g. lack of individual time-activity data). To assess the exposure estimation error in areas with sparse monitoring networks, taking into account specific area pollution characteristics e.g. characterization of the sources; the sub-optimal monitor placement in representing population exposure. To compare the performance of the models, in real and/or simulated data sets, in estimating the associations between long-term exposures to pollutants and a few health outcomes.
In more detail, pollutants models evaluated include: dispersion modeling based on the CMAQ-urban developed by coupling the WRF, the CMAQ and the ADMS to predict concentrations in a 20m grid and Land Use Regression models (LUR) possibly including input from satellite data. These estimated modeled exposure data will be compared to measurements for the full monitoring network and the differences (errors) will be estimated.
The proposal will focus on 3 different areas in the UK, selected with specific criteria, including urban and rural areas and varying population density. As an example, Inner London (14 Boroughs), Manchester Metropolitan Area and Glasgow and Edinburgh Metropolitan Areas may be included, which will comprise of urban, industrial and rural parts. For these areas, health data from routinely maintained data bases (such as mortality by region, incidence of COPD, asthma, ischemic heart disease) or from identified cohort studies may be obtained and the exposure-response associations estimated and compared. The impact of these errors on the health effect estimates will be evaluated.
In addition to the above, or alternatively, a simulated data set for the 3 areas can be generated, based on exposure –response functions from the literature. In the simulated data set the “true” effect is known. This data set will provide the opportunity to evaluate the effect of measurement errors directly on health effect estimates and maybe result in proposing correction factors for estimates from observational studies.
The project will quantify the sensitivity of risk estimates to different exposure models and this information will be used to inform policy on air pollution and health in the context of risk estimates from previous "single-model" approaches.
The Studentship will be based at the Analytical and Environmental Sciences Division (King’s College London) http://www.kcl.ac.uk/lsm/research/divisions/aes/index.aspx for 3 years. The position has a stipend of £16,296 plus tuition fees.
Estimated start date early 2017.
How to Apply:
Click on the link for the application form http://www.environment-health.ac.uk/sites/default/files/Application form for King%27s PhD studentship.docx
All completed applications forms must be submitted by this date to be considered
The application form should be completed and e-mailed to [Email Address Removed]
The title of the project should be placed in the email heading.
Incomplete applications will not be considered.
Eligibility
Applicants are expected to hold a first class or upper second class honours degree (or its equivalent) in an appropriate science subject from a recognised university with a strong quantitative/computational background in biostatistics, epidemiology, data sciences, bioinformatics or mathematics and also have a Masters degree or equivalent research experience by the start of their PhD.
To be eligible for fully funded PhD Studentships, applicants must have a UK or EU nationality.
Then they should meet the following residency criteria:
1) UK residency status or
2) been ‘ordinarily resident’ in the UK for three years prior to the start of the studentship. This means you must normally have been residing in the UK.
If none of the residency criteria apply to you, but you are an EU resident, you may apply for a fees-only studentship. Non-EU international students will not be eligible.
Please note that your residency selections will be verified as part of the application process.
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