Topic outline

  • Course summary

    Ricardo’s openair essentials online training course is designed to help you gain the skills you need to become a confident air quality practitioner.

    Learners are encouraged to submit queries to course trainers both inside and outside of training, over the three days so that exercises and discussion points can be better tailored to address particular areas of interest.

    • Day 1 - An introduction to openair

      Monday 15 May, 10.00am - 3.00pm, online (Zoom)

      Morning: R & RStudio bootcamp (2 hrs)

      You will be introduced to the R programming language. You’ll quickly be brought up to speed with the necessary skills to import and handle data within RStudio and gain a good understanding of what R is and what it can be used for.

      Afternoon: The openair way (2 hrs)

      Next, we’ll introduce the “openair” package, an internationally widely used set of tools for air quality data analysis. You’ll learn about the key tools and data made available via openair and put your new skills into action by investigating real air quality data.

      • Day 2 - Directional Analysis

        Tuesday 16 May, 10.00am - 3.00pm, online (Zoom)

        Morning: Introduction to bivariate polar plots (2hrs)

        On day 2, we will explore the use of more advanced “directional analysis” tools to gain further insight from your data. You’ll be introduced to the bivariate polar plot, a powerful set of methods to understand sources of air pollution.

        Afternoon: Extending polar plots: clustering & mapping (2hrs)

        In the afternoon, we will expand on the content from the morning session, covering how polar data can be clustered to help identify source characteristics in underlying time series. You’ll also be shown how to present your directional analysis on interactive maps, which allow for additional insights as well as being an attractive way to present your analysis to others.

        • Day 3 - Trend Analysis & Open Sessions

          Wednesday 17 May, 10.00am - 3.00pm, online (Zoom)

          *Attendees are encouraged to bring their own data on day 3 to work with in practical exercises, so that the content covered can be applied to their day-to-day work.

          Morning: Meteorological normalisation (2 hrs)

          On the final day, we will explore a powerful method for trend analysis; “meteorological normalisation”. This technique uses a machine learning approach to remove the influence of meteorology in air pollution trends, which is useful to, for example, quantify the effects of an air quality intervention.

          Afternoon: Work in practice (2 hrs)

          The final session is directed by you; David and Jack will be on hand to guide you in analysing your own data, with the online format allowing for whole group discussions and for you to learn from the questions of other learners. By the end of the final day, you’ll be ready to apply your new knowledge in your everyday work and continued future use of R and openair.