A selective diesel vehicle ban’s impact on NO2 concentrations in Munich: a quasi-experimental study

Abstract Background The European Union’s current NO2 concentration limit of 40 μg/m³ is regularly exceeded in Munich, Germany. This limit is likely to be reduced towards the WHO recommended target of 10 μg/m³. In response, the city enacted a selective ban on older diesel vehicles, specifically those categorized as Euro 4 or older, within the current low-emission zone in February 2023. Our study examined how Munich’s selective ban on diesel vehicles impacted NO2 levels, concentrating on the six-month period after its introduction. Methods We employed a synthetic control approach in the primary analysis and a controlled interrupted time series approach in the secondary analysis. These quasi-experimental methods establish a ‘counterfactual’ no-intervention scenario, allowing for comparison with the actual observed scenario and estimation of the impact of the intervention. Historical data from monitoring stations within and outside the low-emission zone from 2014 to 2022 were utilized as controls, while potential confounders were considered. Results NO2 concentrations within Munich’s low-emission zone decreased across the study period. Effects of the selective diesel vehicle ban at monitoring stations within the low-emission zone were minimal, with wide confidence intervals indicating uncertainty. At Landshuter Allee, the average intervention effect was -2.67 μg/m3 (95%-CI = [-12.72; 7.38]), at Stachus it was -2.74 μg/m3 (95%-CI = [-9.91; 4.42]) and at Lothstrasse, it was -1.03 μg/m3 (95%-CI = [-7.75; 5.69]). The secondary analysis confirms these findings. Conclusions Munich’s selective diesel vehicle ban had limited effects in reducing NO2 concentrations. Factors such as its narrow focus on Euro 4 diesel vehicles, numerous exemptions, and unclear enforcement may explain this outcome. Comprehensive strategies and continuous monitoring and evaluation are crucial for effectively addressing urban air pollution and protecting public health. Key messages • Munich’s selective diesel vehicle ban had minimal effects on reducing NO2 levels, possibly due to its narrow scope, many exemptions, and unclear enforcement. • Current guidelines and court rulings signal the need for more effective solutions beyond selective bans, emphasizing the importance of well-designed interventions and rigorous evaluation.

Authors

Institutions

Publication Details

Journal
European Journal of Public Health
Published
2024-10-28
DOI
https://doi.org/10.1093/eurpub/ckae144.916
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A selective diesel vehicle ban’s impact on NO2 concentrations in Munich: a quasi-experimental study

E Rehfuess, Anna Leibinger, Jacob Burns
European Journal of Public Health
Vehicle emissions and performance
article

A selective diesel vehicle ban’s impact on NO2 concentrations in Munich: a quasi-experimental study

E Rehfuess, Anna Leibinger, Jacob Burns
article en

Abstract

Abstract Background The European Union’s current NO2 concentration limit of 40 μg/m³ is regularly exceeded in Munich, Germany. This limit is likely to be reduced towards the WHO recommended target of 10 μg/m³. In response, the city enacted a selective ban on older diesel vehicles, specifically those categorized as Euro 4 or older, within the current low-emission zone in February 2023. Our study examined how Munich’s selective ban on diesel vehicles impacted NO2 levels, concentrating on the six-month period after its introduction. Methods We employed a synthetic control approach in the primary analysis and a controlled interrupted time series approach in the secondary analysis. These quasi-experimental methods establish a ‘counterfactual’ no-intervention scenario, allowing for comparison with the actual observed scenario and estimation of the impact of the intervention. Historical data from monitoring stations within and outside the low-emission zone from 2014 to 2022 were utilized as controls, while potential confounders were considered. Results NO2 concentrations within Munich’s low-emission zone decreased across the study period. Effects of the selective diesel vehicle ban at monitoring stations within the low-emission zone were minimal, with wide confidence intervals indicating uncertainty. At Landshuter Allee, the average intervention effect was -2.67 μg/m3 (95%-CI = [-12.72; 7.38]), at Stachus it was -2.74 μg/m3 (95%-CI = [-9.91; 4.42]) and at Lothstrasse, it was -1.03 μg/m3 (95%-CI = [-7.75; 5.69]). The secondary analysis confirms these findings. Conclusions Munich’s selective diesel vehicle ban had limited effects in reducing NO2 concentrations. Factors such as its narrow focus on Euro 4 diesel vehicles, numerous exemptions, and unclear enforcement may explain this outcome. Comprehensive strategies and continuous monitoring and evaluation are crucial for effectively addressing urban air pollution and protecting public health. Key messages • Munich’s selective diesel vehicle ban had minimal effects on reducing NO2 levels, possibly due to its narrow scope, many exemptions, and unclear enforcement. • Current guidelines and court rulings signal the need for more effective solutions beyond selective bans, emphasizing the importance of well-designed interventions and rigorous evaluation.

European Journal of Public HealthVol. 34(Supplement_3)
LMU Klinikum (DE), Technical University of Munich (DE), Ludwig-Maximilians-Universität München (DE)
Sustainable cities and communities
Openalex Percentile: Top 80%
Vehicle emissions and performance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.