Dataset Information

Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns.

ABSTRACT: The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO₂, O₃, and PM_2.5 concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO₂ concentrations and increases in O₃ were observed in almost all cities. However, the decline in NO₂ concentrations attributable to the lockdowns was not as large as expected, at reductions of 10 to 50%. Accordingly, O₃ increased by 2 to 30% (except for London), the total gaseous oxidant (O _x = NO₂ + O₃) showed limited change, and PM_2.5 concentrations decreased in most cities studied but increased in London and Paris. Our results demonstrate the need for a sophisticated analysis to quantify air quality impacts of interventions and indicate that true air quality improvements were notably more limited than some earlier reports or observational data suggested.

SUBMITTER: Shi Z

PROVIDER: S-EPMC7806219 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns.

Shi Zongbo Z Song Congbo C Liu Bowen B Lu Gongda G Xu Jingsha J Van Vu Tuan T Elliott Robert J R RJR Li Weijun W Bloss William J WJ Harrison Roy M RM

Science advances 20210113 3

The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO2, O3, and PM2.5 concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO2 concentrations and increases in O3 were observed in almost all cities. However, the decline in NO2 concentrations attributab ...[more]

PMID: 33523881

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Project description:This study investigates changes in air quality conditions during the restricted COVID-19 lockdown period in 2020 across 21 metropolitan areas in the Middle East and how these relate to surface urban heat island (SUHI) characteristics. Based on satellite observations of atmospheric gases from Sentinel-5, results indicate significant reductions in the levels of atmospheric pollutants, particularly nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO). Air quality improved significantly during the middle phases of the lockdown (April and May), especially in small metropolitan cities like Amman, Beirut, and Jeddah, while it was less significant in "mega" cities like Cairo, Tehran, and Istanbul. For example, the concentrations of NO2 in Amman, Beirut, and Jeddah decreased by -56.6%, -43.4%, and -32.3%, respectively, during April 2020, compared to April 2019. Rather, there was a small decrease in NO2 levels in megacities like Tehran (-0.9%) and Cairo (-3.1%). Notably, during the lockdown period, there was a decrease in the mean intensity of nighttime SUHI, while the mean intensity of daytime SUHI experienced either an increase or a slight decrease across these locations. Together with the Gulf metropolitans (e.g. Kuwait, Dubai, and Muscat), the megacities (e.g. Tehran, Ankara, and Istanbul) exhibited anomalous increases in the intensity of daytime SUHI, which may exceed 2 °C. Statistical relationships were established to explore the association between changes in the mean intensity and the hotspot area in each metropolitan location during the lockdown. The findings indicate that the mean intensity of SUHI and the spatial extension of hotspot areas within each metropolitan had a statistically significant negative relationship, with Pearson's r values generally exceeding - 0.55, especially for daytime SUHI. This negative dependency was evident for both daytime and nighttime SUHI during all months of the lockdown. Our findings demonstrate that the decrease in primary pollutant levels during the lockdown contributed to the decrease in the intensity of nighttime SUHIs in the Middle East, especially in April and May. Changes in the characteristics of SUHIs during the lockdown period should be interpreted in the context of long-term climate change, rather than just the consequence of restrictive measures. This is simply because short-term air quality improvements were insufficient to generate meaningful changes in the region's urban climate.

Dataset Information

Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns.

Publications

Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns.

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