Learning from the COVID-19 lockdown in berlin: Observations and modelling to support understanding policies to reduce NO2.

Abstract

Urban air pollution is a substantial threat to human health. Traffic emissions remain a large contributor to air pollution in urban areas. The mobility restrictions put in place in response to the COVID-19 pandemic provided a large-scale real-world experiment that allows for the evaluation of changes in traffic emissions and the corresponding changes in air quality. Here we use observational data, as well as modelling, to analyse changes in nitrogen dioxide, ozone, and particulate matter resulting from the COVID-19 restrictions at the height of the lockdown period in Spring of 2020. Accounting for the influence of meteorology on air quality, we found that reduction of ca. 30–50 % in traffic counts, dominated by changes in passenger cars, corresponded to reductions in median observed nitrogen dioxide concentrations of ca. 40 % (traffic and urban background locations) and a ca. 22 % increase in ozone (urban background locations) during weekdays. Lesser reductions in nitrogen dioxide concentrations were observed at urban background stations at weekends, and no change in ozone was observed. The modelled reductions in median nitrogen dioxide at urban background locations were smaller than the observed reductions and the change was not significant. The model results showed no significant change in ozone on weekdays or weekends. The lack of a simulated weekday/weekend effect is consistent with previous work suggesting that NOx emissions from traffic could be significantly underestimated in European cities by models. These results indicate the potential for improvements in air quality due to policies for reducing traffic, along with the scale of reductions that would be needed to result in meaningful changes in air quality if a transition to sustainable mobility is to be seriously considered. They also confirm once more the highly relevant role of traffic for air quality in urban areas.

Seasonal Variations and Effect of COVID-19 Lockdown Restrictions on the Air Quality in the Cities of Kazakhstan

“…This drop can be attributed to the limitations imposed on transport usage in the cities, where in all cities, except Atyrau, only life-supporting facilities and delivery of essential goods were allowed to operate during the lockdown. Similar reductions have been reported in many other cities around the world, such as Wuhan (57%) (Pei et al 2020 ), Berlin (40%) (von Schneidemesser et al 2021 ), Madrid (50%) (Baldasano 2020 ), Barcelona (62%) (Baldasano 2020 ), New York (40%) (Chen et al 2020a ) and others. In other studied cities, the change in NO 2 concentrations during the lockdown period was insignificant compared to the same period in 2018–2019.…”

“…However, the impact of lockdown measures was not uniform across different pollutants and areas. Some studies found insignificant changes in SO 2 or PM 10 concentrations (Pei et al 2020 ; Kerimray et al 2020b ; Assanov et al 2021a ; von Schneidemesser et al 2021 ; Bontempi et al 2022 ), which can be explained by the contribution of the non-traffic emissions sources. Despite the decrease in primary pollutants concentrations, it was observed that secondary pollutants levels, such as O 3 increased (Li and Tartarini 2020 ; Sharma et al 2020 ; Kerimray et al 2020b ; Bera et al 2021 ; von Schneidemesser et al 2021 ; Lou et al 2022 ).…”

“…Some studies found insignificant changes in SO 2 or PM 10 concentrations (Pei et al 2020 ; Kerimray et al 2020b ; Assanov et al 2021a ; von Schneidemesser et al 2021 ; Bontempi et al 2022 ), which can be explained by the contribution of the non-traffic emissions sources. Despite the decrease in primary pollutants concentrations, it was observed that secondary pollutants levels, such as O 3 increased (Li and Tartarini 2020 ; Sharma et al 2020 ; Kerimray et al 2020b ; Bera et al 2021 ; von Schneidemesser et al 2021 ; Lou et al 2022 ). Zangari et al ( 2020 ) showed no changes in air quality in New York City (USA) during the COVID-19 pandemic and assumed that improvement in air quality could occur in places with high levels of air pollutants compared to locations with relatively clean air.…”

Meteorological Normalisation Using Boosted Regression Trees to Estimate the Impact of COVID-19 Restrictions on Air Quality Levels

“…To visualise the impacts of traffic restrictions on air pollution, Figure 8 depicts the daily patterns of NO, NO 2 and PM 10 at roadsides during 2020 lockdown (from 14 March to 1 May) and the equivalent period of the previous seven years (2013–2019). In addition, weekdays, weekends and the non-essential activity shutdown period in Spain (from 30 March to 9 April) were considered separately, as it is well known that weekly patterns have also a relevant importance in emissions [ 87 ]. NO and NO 2 levels in the baseline scenario (dashed lines) showed a daily profile characterised by two peaks that are related to rush hours [ 49 ], around 8 a.m. and 8 p.m., hours in which arrivals and departures in work environments, educational centres, shopping centres, etc., take place.…”

Diesel passenger vehicle shares influenced COVID-19 changes in urban nitrogen dioxide pollution

“…For example, Berlin, Germany stands out given the small ∆NO 2 during the pandemic (figure 3). Less than half of Berlin's monitors are located near traffic (figure S13(b)), and a recent study showed the statistical significance of pandemic-related NO 2 reductions varied across different environments for NO 2 monitors [47]. We explored whether ∆NO 2 within individual cities varied across traffic and non-traffic NO 2 monitors, expecting to find a larger decrease at traffic sites.…”