Internship | Air pollution exposure assessment
Location
UtrechtEducation type
university (wo)Type
Internship and graduation projectHours a week
Fulltime – 40Interested?
Apply now
Air pollution is a global problem resulting in 4.2 million premature deaths in 2016 (WHO factsheet) and costs an estimated 8.1 trillion USD in 2019 equivalent to 6.1% of global GDP (Worldbank). Pollution levels increase 8% per year. The latest burden estimates reflect the very significant role air pollution plays in cardiovascular illness and death. Particulate Matter (PM) is a common proxy indicator for air pollution. It affects more people than any other pollutant. Estimations of Years of Life Lost or Disability Adjusted Life Years rely on the combination of simulated air pollution concentration levels and information on health endpoints such as hospital admissions or registered COPD cases. There is currently a mismatch between he spatial and temporal resolution of air pollution information and the information needed for long-term health studies aimed at large groups of people (cohorts). How can we optimize the available information by using regression methods?
What will be your role?
Regression-based methods (e.g. LUR, machine learning etc) are capable of producing models to predict long-term (i.e. annual, monthly) air pollution concentrations. We would like to use emission data with high spatiotomporal to improve the resolution of regression-based methods and produce concentration maps for PM10/PM2.5. The result will be compared with simulations from the air quality model LOTOS_EUROS in which local PM measurement network dates are integrated by data assimilation. To investigate how the higher resolution model affects the potential health impact, the concentration data of the traditional and new algorithm are combined with population information to calculate the modified intake factor, i.e. inhaled pollution by the population, and study the effect on Disability Adjusted Life Years (DALY)
How do you want to contribute to tomorrow's world? How big can your impact be? Come and work at TNO and envision it.
What we expect from you
- Programming skills in R or python, handling of large data sets
- Affinity with air quality
- High motivation, with a curious nature and a taste for problem-solving
- Ability to work autonomously and good social skills to interact with the team and get the information you need.
- You need to be affiliated with a university during the internship for eligibility
What you’ll get in return
TNO as an employer
At TNO we encourage an inclusive work environment, where you can be yourself. Whatever your story and whatever unique qualities you bring to the table. It is by combining our unique strengths and perspectives that we are able to develop innovations that make a real difference in society. Want to know more? Read what steps we are taking in the area of diversity and inclusion.
The selection process
After the first CV selection, the application process will be conducted by the concerning department. TNO will provide a suitable internship agreement. If you have any questions about this vacancy, you can contact the contact person mentioned below.
Due to Covid-19 and the consequent uncertainties and restrictions, students who are not residing in the Netherlands may currently not be able to start an internship or graduation project at TNO.
Has this job opening sparked your interest?
Then we’d like to hear from you! Please contact us for more information about the job or the selection process. To apply, please upload your CV and covering letter using the ‘apply now’ button.
Contact: Bas Henzing
Phone number: +31 (0)6-117 83139
Interested?
Apply now
Dr. Bas Henzing
- (nano) particles
- atmospheric composition
- aerosol observations
- air quality modelling
- and satellite observations
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