An investigation of the impacts of a successful COVID-19 response and meteorology on air quality in New Zealand

Talbot, Nick; Takada, Akika; Bingham, Andrew H.; Elder, Dan; Lay Yee, Samantha; Golubiewski, Nancy E.

The COVID-19 pandemic brought about national restrictions on people's movements, in effect commencing a socially engineered transport emission reduction experiment. In New Zealand during the most restrictive alert level (Level 4), roadside concentrations of nitrogen dioxide (NO(2)) were reduced 48–54% compared to Business-as-usual (BAU) values. NO(2) concentrations rapidly returned to near mean levels as the alert levels decreased and restrictions eased. PM(10) and PM(2.5) responded differently to NO(2) during the different alert levels. This is due to particulates having multiple sources, many of natural origin and therefore less influenced by human activity. PM(10) and PM(2.5) concentrations were reduced during alert level 4 but to a lesser extent than NO(2) and with more variability across regions. Particulate concentrations increased notably during alert level 2 when many airsheds reported concentrations above the BAU means. To provide robust BAU reference concentrations, simple 5-year means were calculated along with predictions from machine learning modelling that, in effect, removed the influence of meteorology on observed concentrations. The results of this study show that latter method was found to be more closely aligned to observed values for NO(2) as well as PM(2.5) and PM(10) away from coastal regions.