Abstract

The COVID-19 pandemic created an extreme natural experiment in which sudden changes in human behavior and economic activity resulted in significant declines in nitrogen oxide (NOx) emissions, immediately after strict lockdowns were imposed. Here we examined the impact of multiple waves and response phases of the pandemic on nitrogen dioxide (NO2) dynamics and the role of meteorology in shaping relative contributions from different emission sectors to NO2 pollution in post-pandemic New York City. Long term (> 3.5 years), high frequency measurements from a network of ground-based Pandora spectrometers were combined with TROPOMI satellite retrievals, meteorological data, mobility trends, and atmospheric transport model simulations to quantify changes in NO2 across the New York metropolitan area. The stringent lockdown measures after the first pandemic wave resulted in a decline in top-down NOx emissions by approx. 30 % on top of long-term trends, in agreement with sector-specific changes in NOx emissions. Ground-based measurements showed a sudden drop in total column NO2 in spring 2020, by up to 36 % in Manhattan and 19–29 % in Queens, New Jersey and Connecticut, and a clear weakening (by 16 %) of the typical weekly NO2 cycle. Extending our analysis to more than a year after the initial lockdown captured a gradual recovery in NO2 across the NY/NJ/CT tri-state area in summer and fall 2020, as social restrictions eased, followed by a second decline in NO2 coincident with the second wave of the pandemic and resurgence of lockdown measures in winter 2021. Meteorology was not found to have a strong NO2 biasing effect in New York City after the first pandemic wave. Winds, however, were favorable for low NO2 conditions in Manhattan during the second wave of the pandemic, resulting in larger column NO2 declines than expected based on changes in transportation emissions alone. Meteorology played a key role in shaping the relative contributions from different emission sectors to NO2 pollution in the city, with low-speed (< 5 ms−1) SW-SE winds enhancing contributions from the high-emitting power-generation sector in NJ and Queens and driving particularly high NO2 pollution episodes in Manhattan, even during – and despite – the stringent early lockdowns. These results have important implications for air quality management in New York City, and highlight the value of high resolution NO2 measurements in assessing the effects of rapid meteorological changes on air quality conditions and the effectiveness of sector-specific NOx emission control strategies.

Highlights

  • The global outbreak of the Coronavirus Disease 2019 (COVID-19) profoundly changed the world

  • Reporting a decline in Tropospheric Monitoring Instrument (TROPOMI) NO2 column by 28(±11)% within a 100-km radius around New York City during the three weeks following the onset of the pandemic compared to the same period in 2019

  • For 25 April, we find that the largest contribution of nitrogen oxide (NOx) at the Manhattan site is from power generation (42%), with manufacturing dominating at the Queens site (30%)

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Summary

Introduction

The global outbreak of the Coronavirus Disease 2019 (COVID-19) profoundly changed the world. Altered mobility patterns led to sudden and significant worldwide decreases in nitrogen oxide (NOx) emissions from the transportation sector, as documented in many studies focusing on air quality changes immediately after the initial lockdowns (e.g., Liu et al., 2020; Goldberg et al, 2020; Gkatzelis et al, 2021). The impact of multiple pandemic waves over longer time periods, and the role of meteorology and sector-specific emissions as key drivers of high NOx pollution episodes that occurred in major cities such as New York - even during, and despite, the most stringent early lockdown periods - remain largely unknown, driving this study. New York City, the most populous and most densely populated city in the Unites States, was hit hard by the pandemic. By late-March 2020, the tri-state region of New York (NY), New Jersey (NJ) and Connecticut (CT)

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