Dataset Information

COVID-19 mitigation measures and nitrogen dioxide - A quasi-experimental study of air quality in Munich, Germany.

ABSTRACT:

Background

In response to the COVID-19 pandemic, the Bavarian State government announced several COVID-19 mitigation measures beginning on March 16, 2020, which likely led to a reduction in traffic and a subsequent improvement in air quality. In this study, we evaluated the short-term effect of COVID-19 mitigation measures on NO₂ concentrations in Munich, Germany.

Methods

We applied two quasi-experimental approaches, a controlled interrupted time-series (c-ITS) approach and a synthetic control (SC) approach. Each approach compared changes occurring in 2020 to changes occurring in 2014-2019, and accounted for weather-related and other potential confounders. We hypothesized that the largest reductions in NO₂ concentrations would be observed at traffic sites, with smaller reductions at urban background sites, and even small reductions, if any, at background sites. All hypotheses, as well as the main and additional analyses were defined a priori. We also conducted post-hoc analyses to ensure that observed effects were not due to factors other than the intervention.

Results

Main analyses largely supported our hypotheses. Specifically, at the two traffic sites, using the c-ITS approach we observed reductions of 9.34 ?g/m³ (95% confidence interval: -23.58; 4.90) and 10.02 ?g/m³ (-19.25; -0.79). Using the SC approach we observed reductions of 15.65 ?g/m³ (-27.58; -4.09) and 15.1 ?g/m³ (-24.82; -9.83) at these same sites. We observed effects ranging from smaller in magnitude to no effect at urban background and background sites. Additional analyses showed that the effect was largest in the first two weeks following introduction of measures, and that a 3-day lagged intervention time also showed a larger effect. Post-hoc analyses suggested that at least some of the observed effects may have been attributable to changes in air quality occurring before the intervention, as well as unusually high concentrations in January 2020.

Conclusion

We applied two quasi-experimental approaches in assessing the impact of the COVID-19 mitigation measures on NO₂ concentrations in Munich. Taking the 2020 pre-intervention average concentrations as a reference, we observed reductions in NO₂ concentrations of approximately 15-25% and 24-36% at traffic sites, suggesting that reducing traffic may be an effective measure to reduce NO₂ concentrations in heavily trafficked areas by margins which could translate to public health benefits.

SUBMITTER: Burns J

PROVIDER: S-EPMC7680620 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

COVID-19 mitigation measures and nitrogen dioxide - A quasi-experimental study of air quality in Munich, Germany.

Burns Jacob J Hoffmann Sabine S Kurz Christoph C Laxy Michael M Polus Stephanie S Rehfuess Eva E

Atmospheric environment (Oxford, England : 1994) 20201122

<h4>Background</h4>In response to the COVID-19 pandemic, the Bavarian State government announced several COVID-19 mitigation measures beginning on March 16, 2020, which likely led to a reduction in traffic and a subsequent improvement in air quality. In this study, we evaluated the short-term effect of COVID-19 mitigation measures on NO<sub>2</sub> concentrations in Munich, Germany.<h4>Methods</h4>We applied two quasi-experimental approaches, a controlled interrupted time-series (c-ITS) approach ...[more]

PMID: 33250657

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Project description:BackgroundPreterm birth is the leading cause of child mortality globally, with many survivors experiencing long-term adverse consequences. Preliminary evidence suggests that numbers of preterm births greatly reduced following implementation of policy measures aimed at mitigating the effects of the COVID-19 pandemic. We aimed to study the impact of the COVID-19 mitigation measures implemented in the Netherlands in a stepwise fashion on March 9, March 15, and March 23, 2020, on the incidence of preterm birth.MethodsWe used a national quasi-experimental difference-in-regression-discontinuity approach. We used data from the neonatal dried blood spot screening programme (2010-20) cross-validated against national perinatal registry data. Stratified analyses were done according to gestational age subgroups, and sensitivity analyses were done to assess robustness of the findings. We explored potential effect modification by neighbourhood socioeconomic status, sex, and small-for-gestational-age status.FindingsData on 1 599 547 singleton neonates were available, including 56 720 births that occurred after implementation of COVID-19 mitigation measures on March 9, 2020. Consistent reductions in the incidence of preterm birth were seen across various time windows surrounding March 9 (± 2 months [n=531 823] odds ratio [OR] 0·77, 95% CI 0·66-0·91, p=0·0026; ± 3 months [n=796 531] OR 0·85, 0·73-0·98, p=0·028; ± 4 months [n=1 066 872] OR 0·84, 0·73-0·97, p=0·023). Decreases in incidence observed following the March 15 measures were of smaller magnitude, but not statistically significant. No changes were observed after March 23. Reductions in the incidence of preterm births after March 9 were consistent across gestational age strata and robust in sensitivity analyses. They appeared confined to neighbourhoods of high socioeconomic status, but effect modification was not statistically significant.InterpretationIn this national quasi-experimental study, initial implementation of COVID-19 mitigation measures was associated with a substantial reduction in the incidence of preterm births in the following months, in agreement with preliminary observations elsewhere. Integration of comparable data from across the globe is needed to further substantiate these findings and start exploring underlying mechanisms.FundingNone.

Project description:BackgroundLockdowns amid the COVID-19 pandemic have offered a real-world opportunity to better understand air quality responses to previously unseen anthropogenic emission reductions.Methods and main objectiveThis work examines the impact of Vienna's first lockdown on ground-level concentrations of nitrogen dioxide (NO2), ozone (O3) and total oxidant (Ox). The analysis runs over January to September 2020 and considers business as usual scenarios created with machine learning models to provide a baseline for robustly diagnosing lockdown-related air quality changes. Models were also developed to normalise the air pollutant time series, enabling facilitated intervention assessment.Core findingsNO2 concentrations were on average -20.1% [13.7-30.4%] lower during the lockdown. However, this benefit was offset by amplified O3 pollution of +8.5% [3.7-11.0%] in the same period. The consistency in the direction of change indicates that the NO2 reductions and O3 increases were ubiquitous over Vienna. Ox concentrations increased slightly by +4.3% [1.8-6.4%], suggesting that a significant part of the drops in NO2 was compensated by gains in O3. Accordingly, 82% of lockdown days with lowered NO2 were accompanied by 81% of days with amplified O3. The recovery shapes of the pollutant concentrations were depicted and discussed. The business as usual-related outcomes were broadly consistent with the patterns outlined by the normalised time series. These findings allowed to argue further that the detected changes in air quality were of anthropogenic and not of meteorological reason. Pollutant changes on the machine learning baseline revealed that the impact of the lockdown on urban air quality were lower than the raw measurements show. Besides, measured traffic drops in major Austrian roads were more significant for light-duty than for heavy-duty vehicles. It was also noted that the use of mobility reports based on cell phone movement as activity data can overestimate the reduction of emissions for the road transport sector, particularly for heavy-duty vehicles. As heavy-duty vehicles can make up a large fraction of the fleet emissions of nitrogen oxides, the change in the volume of these vehicles on the roads may be the main driver to explain the change in NO2 concentrations.Interpretation and implicationsA probable future with emissions of volatile organic compounds (VOCs) dropping slower than emissions of nitrogen oxides could risk worsened urban O3 pollution under a VOC-limited photochemical regime. More holistic policies will be needed to achieve improved air quality levels across different regions and criteria pollutants.

Dataset Information

COVID-19 mitigation measures and nitrogen dioxide - A quasi-experimental study of air quality in Munich, Germany.

Background

Methods

Results

Conclusion

Publications

COVID-19 mitigation measures and nitrogen dioxide - A quasi-experimental study of air quality in Munich, Germany.

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