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• W3160882754 abstract "We propose a new approach to estimate the causal effects of maritime traffic when natural or policy experiments are not available. We apply this method to the case of Marseille, a large Mediterranean port city, where air pollution emitted by cruise vessels is a growing concern. Using a recent matching algorithm designed for time series data, we create hypothetical randomized experiments to estimate the change in local air pollution caused by a short-term increase in cruise traffic. We then rely on randomization inference to compute nonparametric 95% uncertainty intervals. We find that cruise vessels' arrivals have large impacts on city-level hourly concentrations of nitrogen dioxide, particulate matter, and sulfur dioxide. At the daily level, road traffic seems however to have a much larger impact than cruise traffic. Our procedure also helps assess in a transparent manner the identification challenges specific to this type of high-frequency time series data." @default.
• W3160882754 created "2021-05-24" @default.
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• W3160882754 date "2021-04-19" @default.
• W3160882754 modified "2023-09-27" @default.
• W3160882754 title "Estimating the Causal Effects of Cruise Traffic on Air Pollution using Randomization-Based Inference" @default.
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• W3160882754 doi "https://doi.org/10.31219/osf.io/v7ctk" @default.
• W3160882754 hasPublicationYear "2021" @default.
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