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Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019
Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019
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Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019
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Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019
Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019

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Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019
Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019
Journal Article

Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019

2021
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Overview
Emission inventory development for air pollutants, by compiling records from individual emission sources, takes many years and involves extensive multi-national effort. A complementary method to estimate air pollution emissions is in the use of satellite remote sensing. In this study, NO 2 observations from the Ozone Monitoring Instrument are combined with re-analysis meteorology to estimate urban nitrogen oxide (NO X ) emissions for 80 global cities between 2005 and 2019. The global average downward trend in satellite-derived urban NO X emissions was 3.1%–4.0% yr −1 between 2009 and 2018 while inventories show a 0%–2.2% yr −1 drop over the same timeframe. This difference is primarily driven by discrepancies between satellite-derived urban NO X emissions and inventories in Africa, China, India, Latin America, and the Middle East. In North America, Europe, Korea, Japan, and Australasia, NO X emissions dropped similarly as reported in the inventories. In Europe, Korea, and Japan only, the temporal trends match the inventories well, but the satellite estimate is consistently larger over time. While many of the discrepancies between satellite-based and inventory emissions estimates represent real differences, some of the discrepancies might be related to the assumptions made to compare the satellite-based estimates with inventory estimates, such as the spatial disaggregation of emissions inventories. Our work identifies that the three largest uncertainties in the satellite estimate are the tropospheric column measurements, wind speed and direction, and spatial definition of each city.