Project Proposal
The Ultra-Low Emission Zone (ULEZ) is a zone consisting of strict vehicular emission standards and a toll charge of £12.50 per day for access implemented in central London in April of 2019 (Greater London Authority, 2019b). Approximately half of the emissions in London from vehicular transport are nitrogen oxides (NOx) which can lead to exceedances of nitrogen dioxide (NO2), a pollutant of concern for London (Greater London Authority, 2019b). Given that NO2 is associated with increasing prevalence of respiratory problems in addition to premature deaths, the Mayor of London implemented the ULEZ. So far, the ULEZ has had tremendous success. Between April and June of 2019, there was a 24% decrease in NO2 in Central London and a 10% decrease in Inner London (Greater London Authority, 2019a). In Canada, approximately 10,000 people die prematurely on a yearly basis due to air pollution and there is a 5% increase in risk of mortality in moving to urban centres such as Vancouver as explained by Michael Brauer, a professor and researcher in occupational and environmental health (Uguen-Csenge, 2019). Given the success of the ULEZ, this report aims to determine the need and practicality of implementing this zone in Metro Vancouver.
Project Management
In order to organize and complete this project efficiently, we divide the work. In the mapping process, two people focussed on the actual mapping, while one person focussed on documenting the methodological process. In writing the report on the other hand, we divided it so that one person focussed on the methods, the flowchart, and the description one person focussed on the results and discussion, and one person focussed on the errors, future recommendations, and the abstract. However, we still contributed to components of the report that we weren’t initially tasked to work on.
Key Learnings
Completing this project was a very awesome learning process. Given that we hadn’t previously worked with air quality data in the labs, there was a bit of a learning curve to adapt. It was particularly interesting using this data because there was a lot of missing data and uncertainty associated with this data that I don’t feel like we had previously been exposed to in the previous labs. For the air quality station data there were air stations included that did not have any air quality data and there were some air stations included that no longer operate. The air quality dataset also had many values missing. Thus, this project made me realize that there has to be a lot of consideration for errors and uncertainty when making maps and it would be beneficial to provide a statement explaining this alongside a map to ensure that it is not taken at face value.