Abstract
Abstract. This study quantifies the impact of emission changes during public holidays on air quality (AQ) and analyses the added value of accounting for the holidays in AQ modelling. Spatial and temporal distributions of atmospheric concentrations of the major air pollutants (the main focus was on NO2, but we also included O3, CO, PM2.5, and SO2) were considered at the European scale for all public holidays of 2018. Particular attention was paid to the events with the most pronounced continental- or regional-scale impact: Christmas and New Year, Easter, May Day vacations, and the last days of Ramadan. The simulations were performed with the chemistry transport model SILAM v.5.7 (System for Integrated modeLling of Atmospheric coMposition). Three model runs were made: the baseline with no treatment of holidays, the run considering holidays as Sundays, and the run forcing 80 % reduction in emissions during holidays for the weekday-sensitive sectors. The emission scaling was applied on a country basis. The model predictions were compared with in situ observations collected by the European Environment Agency. The experiment showed that even conservative treatment of official holidays has a large positive impact on NOx (up to 30 % of reduction in the bias inhomogeneity during the holiday days) and improves the CO, PM2.5, and O3 predictions. In many cases, the sensitivity simulations suggested a greater emission reduction than the level of Sundays. An individual consideration of the holiday events in different countries may further improve their representation in the models: specific diurnal pattern of emissions, additional emission due to fireworks, and different driving patterns.
Highlights
Air quality (AQ) and its temporal and spatial changes are determined by human activities via the release of various air pollutants (Derwent and Hjellbrekke, 2012; Fu et al, 2020; Hassan et al, 2013; Karl et al, 2019; Kukkonen et al, 2020; Lehtomäki et al, 2018; Shi et al, 2019) and modulated by meteorological conditions (Jacob and Winner, 2009; Jhun et al, 2015; Singh et al, 2013; Sofiev et al, 2020)
The simulations presented in the previous section confirmed that the official holidays substantially affect air quality, as shown in the studies outlined in the Introduction
Incorporating information on public holidays in emissions of the affected anthropogenic sectors leads to substantial shortterm improvements of the SILAM model scores, even if done conservatively
Summary
Air quality (AQ) and its temporal and spatial changes are determined by human activities via the release of various air pollutants (Derwent and Hjellbrekke, 2012; Fu et al, 2020; Hassan et al, 2013; Karl et al, 2019; Kukkonen et al, 2020; Lehtomäki et al, 2018; Shi et al, 2019) and modulated by meteorological conditions (Jacob and Winner, 2009; Jhun et al, 2015; Singh et al, 2013; Sofiev et al, 2020).The ability of atmospheric composition models to follow the temporal variability of air pollution critically depends on the representation of temporal emission profiles by inventories used by the models. Changes in human behaviour during non-working days of various type (Beirle et al, 2003; de Foy et al, 2020, 2016; Elansky, 2020; Gour et al, 2013; Hassan et al, 2013; Xu et al, 2017; Zou et al, 2019; Rozbicka and Rozbicki, 2016), including some religious ceremonies (Dasari et al, 2020), cultural practices (Khezri et al, 2015; Nodehi et al, 2018; Ye et al, 2016), celebratory events, and festivities (Hoyos et al, 2020; Jiang et al, 2015; Lai and Brimblecombe, 2017; Retama et al, 2019), cause large variations in emissions of air pollutants, which are hard to quantify and generalize. The majority of currently available emission inventories are built as gridded yearly or monthly totals for the key primary pollutants (Frost et al, 2013; Granier et al, 2019, 2011),
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