Abstract
Abstract. Lockdown and the associated massive reduction in people's mobility imposed by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) mitigation measures across the globe provide a unique sensitivity experiment to investigate impacts on carbon and air pollution emissions. We present an integrated observational analysis based on long-term in situ multispecies eddy flux measurements, allowing for quantifying near-real-time changes of urban surface emissions for key air quality and climate tracers. During the first European SARS-CoV-2 wave we find that the emission reduction of classic air pollutants decoupled from CO2 and was significantly larger. These differences can only be rationalized by the different nature of urban combustion sources and point towards a systematic bias of extrapolated urban NOx emissions in state-of-the-art emission models. The analysis suggests that European policies, shifting residential, public, and commercial energy demand towards cleaner combustion, have helped to improve air quality more than expected and that the urban NOx flux remains to be dominated (e.g., >90 %) by traffic.
Highlights
Managing air pollution and climate change are among the most important environmental challenges of modern society
The quantitative assessment of NOx emissions based on ambient-air concentrations remains challenging due to non-linearities within the NO–NO2–O3 triad in polluted regions (Lenschow et al, 2016)
Our analysis indicates that the reduction of classic air pollutant emissions during the SARS-CoV-2 lockdown was more significant than that of CO2, which comes as a surprise
Summary
Managing air pollution and climate change are among the most important environmental challenges of modern society. As urban population continues to grow, emissions from metropolitan areas play an increasingly important role. European cities already host about 74 % of the population (UN, 2019) and are a major contributor to air pollutant and greenhouse gas emissions. Along with socioeconomic development and without mitigation, can lead to substantial increases in anthropogenic emissions. Many cities are committing to sustainable development goals, and improvement of air pollution and mitigation of climate change are emerging as key sustainability priorities across the globe. Quantifying the diversity of urban emissions is often one of the most uncertain components of complex atmospheric models, and development of a robust predictive capability requires accurate data and careful evaluation of bottom-up emissions (Blain et al, 2019; NAS, 2016)
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