Nitrogen dioxide decline and rebound observed by GOME-2 and TROPOMI during COVID-19 pandemic.

Since its first confirmed case in December 2019, coronavirus disease 2019 (COVID-19) has become a worldwide pandemic with more than 90 million confirmed cases by January 2021. Countries around the world have enforced lockdown measures to prevent the spread of the virus, introducing a temporal change of air pollutants such as nitrogen dioxide (NO2) that are strongly related to transportation, industry, and energy. In this study, NO2 variations over regions with strong responses to COVID-19 are analysed using datasets from the Global Ozone Monitoring Experiment-2 (GOME-2) sensor aboard the EUMETSAT Metop satellites and TROPOspheric Monitoring Instrument (TROPOMI) aboard the EU/ESA Sentinel-5 Precursor satellite. The global GOME-2 and TROPOMI NO2 datasets are generated at the German Aerospace Center (DLR) using harmonized retrieval algorithms; potential influences of the long-term trend and seasonal cycle, as well as the short-term meteorological variation, are taken into account statistically. We present the application of the GOME-2 data to analyze the lockdown-related NO2 variations for morning conditions. Consistent NO2 variations are observed for the GOME-2 measurements and the early afternoon TROPOMI data: regions with strong social responses to COVID-19 in Asia, Europe, North America, and South America show strong NO2 reductions of ∼ 30-50% on average due to restriction of social and economic activities, followed by a gradual rebound with lifted restriction measures. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-021-01046-2.

Pinpointing nitrogen oxide emissions from space.

Satellite observations of nitrogen dioxide (NO2) provide valuable information on the location and strength of NO x emissions, but spatial resolution is limited by horizontal transport and smearing of temporal averages due to changing wind fields. In this study, we map NO x emissions on high spatial resolution from TROPOMI observations of NO2 combined with wind fields based on the continuity equation. The divergence of horizontal fluxes proves to be highly sensitive for point sources like exhaust stacks. Thus, NO x emissions from individual power plants can be resolved and quantified even on top of considerably high urban pollution from the Saudi Arabian capital city Riyadh. This allows us to catalog NO x emissions from large point sources globally, as demonstrated for South Africa and Germany, with a detection limit of about 0.11 kg/s down to 0.03 kg/s for ideal conditions.

Top-Down NOX Emissions of European Cities Based on the Downwind Plume of Modelled and Space-Borne Tropospheric NO2 Columns.

Top-down estimates of surface NOX emissions were derived for 23 European cities based on the downwind plume decay of tropospheric nitrogen dioxide (NO2) columns from the LOTOS-EUROS (Long Term Ozone Simulation-European Ozone Simulation) chemistry transport model (CTM) and from Ozone Monitoring Instrument (OMI) satellite retrievals, averaged for the summertime period (April⁻September) during 2013. Here we show that the top-down NOX emissions derived from LOTOS-EUROS for European urban areas agree well with the bottom-up NOX emissions from the MACC-III inventory data (R² = 0.88) driving the CTM demonstrating the potential of this method. OMI top-down NOX emissions over the 23 European cities are generally lower compared with the MACC-III emissions and their correlation is slightly lower (R² = 0.79). The uncertainty on the derived NO2 lifetimes and NOX emissions are on average ~55% for OMI and ~63% for LOTOS-EUROS data. The downwind NO2 plume method applied on both LOTOS-EUROS and OMI tropospheric NO2 columns allows to estimate NOX emissions from urban areas, demonstrating that this is a useful method for real-time updates of urban NOX emissions with reasonable accuracy.

NOx emission trends over Chinese cities estimated from OMI observations during 2005 to 2015.

Satellite NO2 observations have been widely used to evaluate emission changes. To determine trends in NOx emission over China, we used a method independent of chemical transport models to quantify the NOx emissions from 48 cities and 7 power plants over China, on the basis of Ozone Monitoring Instrument (OMI) NO2 observations during 2005 to 2015. We found that NOx emissions over 48 Chinese cities increased by 52% from 2005 to 2011 and decreased by 21% from 2011 to 2015. The decrease since 2011 could be mainly attributed to emission control measures in power sector; while cities with different dominant emission sources (i.e. power, industrial and transportation sectors) showed variable emission decline timelines that corresponded to the schedules for emission control in different sectors. The time series of the derived NOx emissions was consistent with the bottom-up emission inventories for all power plants (r=0.8 on average), but not for some cities (r=0.4 on average). The lack of consistency observed for cities was most probably due to the high uncertainty of bottom-up urban emissions used in this study, which were derived from downscaling the regional-based emission data to cities by using spatial distribution proxies.

Abrupt recent trend changes in atmospheric nitrogen dioxide over the Middle East.

Nitrogen oxides, released from fossil fuel use and other combustion processes, affect air quality and climate. From the mid-1990s onward, nitrogen dioxide (NO2) has been monitored from space, and since 2004 with relatively high spatial resolution by the Ozone Monitoring Instrument. Strong upward NO2 trends have been observed over South and East Asia and the Middle East, in particular over major cities. We show, however, that a combination of air quality control and political factors, including economical crisis and armed conflict, has drastically altered the emission landscape of nitrogen oxides in the Middle East. Large changes, including trend reversals, have occurred since about 2010 that could not have been predicted and therefore are at odds with emission scenarios used in projections of air pollution and climate change in the early 21st century.

Megacity emissions and lifetimes of nitrogen oxides probed from space.

Megacities are immense sources of air pollutants, with large impacts on air quality and climate. However, emission inventories in many of them still are highly uncertain, particularly in developing countries. Satellite observations allow top-down estimates of emissions to be made for nitrogen oxides (NO(x) = NO + NO(2)), but require poorly quantified a priori information on the NO(x) lifetime. We present a method for the simultaneous determination of megacity NO(x) emissions and lifetimes from satellite measurements by analyzing the downwind patterns of NO(2) separately for different wind conditions. Daytime lifetimes are ~4 hours at low and mid-latitudes, but ~8 hours in wintertime for Moscow. The derived NO(x) emissions are generally in good agreement with existing emission inventories, but are higher by a factor of 3 for the Saudi Arabian capital Riyadh.

Threading neural feedforward into a mechanical spring: how biology exploits physics in limb control.

A solution is proposed of the hitherto unsolved problem as to how neural feedforward through inverse modelling and negative feedback realised by a mechanical spring can be combined to achieve a highly effective control of limb movement. The revised spring approach that we suggest does not require forward modelling and produces simulated data which are as close as possible to experimental human data. Control models based on peripheral sensing with forward modelling, which are favoured in the current literature, fail to create such data. Our approach suggests that current views on motor control and learning should be revisited.