| Grant number: | 12/19266-8 |
| Support Opportunities: | Scholarships in Brazil - Master |
| Start date: | December 01, 2012 |
| End date: | November 30, 2013 |
| Field of knowledge: | Health Sciences - Collective Health - Public Health |
| Principal Investigator: | Paulo Hilário Nascimento Saldiva |
| Grantee: | Lais Fajersztajn |
| Host Institution: | Faculdade de Medicina (FM). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
Abstract There is a large amount of evidences relating environmental air pollution to adverse health effects. 1-8 However, control policies have shown limited effect on air quality, since only 2% of the world urban population are living in areas with acceptable air pollution concentrations according to the World Health Organization Air Quality Guideline.9 A recent report by the Organization for Economic Co-operation and Development (OECD) alerts that air pollution is set to become the world's top environmental cause of premature mortality by 2050, overcoming unsafe water and sanitation, mainly in the BRIICS (Brazil, Russian, Indonesia, India, China and South Africa) and lower income countries. In a previous analysis, we found a marked unevenness in the geographical distribution of scientific publications on air pollution topic. Globally air pollution is also unevenly distributed. We hypothesize that there is a lack of scientific knowledge to underlie air pollution policy interventions and this lack is geographically concentrated where air quality is inadequate. Our aim is to study how science influences air quality in different countries of the world. We will study the correlations between exposure indicators (particulate matter concentration) and global scientific production on air pollution topic. The scientific production will be evaluated at the search platform Web of Science. The countries studied by the scientific articles and the countries that contributed to the authorship of these studies will be identified, as well as occasional international partnerships. We will use descriptive statistics, cluster analysis techniques (clustter) and principal component analysis in order to define the most consistently factors associated with high and low productivity in air pollution topic. (AU) | |
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