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AbstractDuring spring 2020, unprecedented changes in local and regional emissions have occurred around the globe due to governmental restrictions associated with COVID-19. Many European countries including Austria issued partial curfews or stay-at-home order policies, which have impacted ambient air quality through reductions in non-essential transportation and energy consumption of industrial sites and work places. Here, we analyse the effect of these measures on ambient concentrations of nitrogen oxides (NOx), ozone (O3) and particulate matter (PM10) during the first nationwide lockdown in Austria (16.03.2020 to 14.04.2020). To ensure a robust analysis, the Austrian domain is divided into four individual subsectors contingent on regional climate. For air quality analysis a novel method is applied for filtering days with comparable weather conditions during the 2020 lockdown and spring 2017 to 2019. In general, our analysis shows decreasing pollutant concentrations, although in magnitude dependent on pollutant and regional subdomain. Largest reductions are found for NOx reaching up to −68% at traffic sites reflecting the substantial decrease in non-essential transport. Changes in the O3 concentrations at background sites show a rather weak response to NOx declines varying between roughly −18 to +8% for both the median and the upper tail of the distribution. Occasional site level increases in O3 concentrations can be attributed to comparably weak titration during night-time. PM10 concentrations show the smallest response among air pollutants, attributable to manifold precursor sources not affected by the lockdown measures. However, our analysis indicates also a shift of PM10 distributions at traffic sites closer to distributions observed at background sites.

49 pags, 10 figs, 2 tabs. -- Supplementary data is available at the Publisher's web ; The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for the problem being addressed, whether biases can be tolerated or corrected, whether the model is appropriately constituted, and whether there is a way to satisfactorily quantify the uncertainty. ; A portion of the work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the NASA Aeronautics and Space Administration. A portion of the work was carried out the National Center for Atmospheric Research, which is operated by the University Corporation for Atmospheric Research under sponsorship of the National Science Foundation. PY acknowledges support from the Faculty of Science and Technology, Lancaster University. JB and UI acknowledge NordForsk under the Nordic Programme on Health and Welfare Project #75007: Understanding the link between air pollution and distribution of related health impacts and welfare in the Nordic countries (Nordic Welf Air); and the H2020-LCE project: Role of technologies in an energy efficient economy – model based analysis policy measures and transformation pathways to a sustainable energy system (REEEM), Grant agreement no.: 691739. GZ acknowledges the New Zealand Government's Strategic Science Investment Fund (SSIF) through the NIWA programme CACV. This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/N027736/1] and the Natural Environment Research Council [grant number NE/N003411/1]. ; Peer reviewed