The Winter School 2021 on Data Science for Climate and Air Quality Research was held online from December 2021 until February 2022. The Winter School has five sessions which were scheduled from 8:00 or 9:00 am UK time and 4:00 or 5:00 pm China time. The workshops were free to attend; recordings have been made available on this website.
Objectives
- To introduce the theoretical basis of the openair R package and machine learning
- To provide practical training by applying the theory to case studies
- To provide hands-on experience in using existing codes for climate, air quality, health and economics research.
Training Sessions
Session 1: Introduction to openair, 13 Dec 2021
Prof David Carslaw (University of York)
Aim: To introduce openair and its applications in air quality research.
Recording of the session: https://youtu.be/t7vr2mUVTE4
Session 2: Machine learning for intervention studies, 15 Dec 2021
Dr Qili Dai (Nankai University) and Dr Congbo Song (University of Birmingham)
Aim: To introduce recent advances in weather normalization of air pollutant concentrations and their application in policy evaluation.
Recording of the session: https://youtu.be/CHOLTuugjo0
Session 3: Emulation of air quality in China, 6 Jan 2022
Dr Luke Conibear and Prof Dom Spracklen (University of Leeds)
Aim: To provide training in the methods of statistical emulation for air quality research.
Recording of the session: https://youtu.be/zbt7aa2QIAA
Session 4: Data science for air pollution exposure science and personal monitoring, 21 February 2022
Dr Yiqun Han, Dr Hanbin Zhang (Imperial College London), and Dr Lia Chatzidiakou (University of Cambridge)
Aim: To introduce applications of personal sensors in air quality research.
Recording of the session: https://youtu.be/JQaCedyCPPg
Session 5: Machine learning for airborne particle identification from spectral / image datasets, 24 February 2022
Prof David Topping (University of Manchester)
Aim: To introduce the diverse set of tools now used to try and resolve characteristics of particulate matter from instrument response functions.
Recording of the session: https://youtu.be/7c-uMHKvkPI