During the COVID-19 lockdown, the dramatic reduction of anthropogenic
emissions provided a unique opportunity to investigate the effects of
reduced anthropogenic activity and primary emissions on ...atmospheric chemical
processes and the consequent formation of secondary pollutants. Here, we
utilize comprehensive observations to examine the response of atmospheric
new particle formation (NPF) to the changes in the atmospheric chemical
cocktail. We find that the main clustering process was unaffected by the
drastically reduced traffic emissions, and the formation rate of 1.5 nm
particles remained unaltered. However, particle survival probability was
enhanced due to an increased particle growth rate (GR) during the lockdown
period, explaining the enhanced NPF activity in earlier studies. For GR at
1.5–3 nm, sulfuric acid (SA) was the main contributor at high temperatures,
whilst there were unaccounted contributing vapors at low temperatures. For
GR at 3–7 and 7–15 nm, oxygenated organic molecules (OOMs) played a
major role. Surprisingly, OOM composition and volatility were insensitive to
the large change of atmospheric NOx concentration; instead the
associated high particle growth rates and high OOM concentration during the
lockdown period were mostly caused by the enhanced atmospheric oxidative
capacity. Overall, our findings suggest a limited role of traffic emissions
in NPF.
Satellite measurements in nadir and limb viewing geometry provide a complementary view of the atmosphere. An effective combination of the limb and nadir measurements can give new information about ...atmospheric composition. In this work, we present tropospheric ozone column datasets that have been created using a combination of total ozone columns from OMI (Ozone Monitoring Instrument) and TROPOMI (TROPOspheric Monitoring Instrument) with stratospheric ozone column datasets from several available limb-viewing instruments: MLS (Microwave Limb Sounder), OSIRIS (Optical Spectrograph and InfraRed Imaging System), MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), SCIAMACHY (SCanning Imaging Spectrometer for Atmospheric CHartographY), OMPS-LP (Ozone Mapping and Profiles Suite - Limb Profiler), and GOMOS (Global Ozone Monitoring by Occultation of Stars).
In this paper, we present a merged dataset of ozone profiles from several satellite instruments: SAGE II on ERBS, GOMOS, SCIAMACHY and MIPAS on Envisat, OSIRIS on Odin, ACE-FTS on SCISAT, and OMPS on ...Suomi-NPP. The merged dataset is created in the framework of the European Space Agency Climate Change Initiative (Ozone_cci) with the aim of analyzing stratospheric ozone trends. For the merged dataset, we used the latest versions of the original ozone datasets. The datasets from the individual instruments have been extensively validated and intercompared; only those datasets which are in good agreement, and do not exhibit significant drifts with respect to collocated ground-based observations and with respect to each other, are used for merging. The long-term SAGE–CCI–OMPS dataset is created by computation and merging of deseasonalized anomalies from individual instruments. The merged SAGE–CCI–OMPS dataset consists of deseasonalized anomalies of ozone in 10° latitude bands from 90° S to 90° N and from 10 to 50 km in steps of 1 km covering the period from October 1984 to July 2016. This newly created dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997. The upper stratospheric trends are statistically significant at midlatitudes and indicate ozone recovery, as expected from the decrease of stratospheric halogens that started in the middle of the 1990s and stratospheric cooling.
In this paper, we discuss the method for validation of random uncertainties in the remote sensing measurements based on evaluation of the structure function, i.e., root-mean-square differences as a ...function of increasing spatiotemporal separation of the measurements. The limit at the zero mismatch provides the experimental estimate of random noise in the data. At the same time, this method allows probing of the natural variability of the measured parameter. As an illustration, we applied this method to the clear-sky total ozone measurements by the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5P satellite.
Carbon monoxide (CO) has negative health effects, especially on the respiratory system, when present in large concentrations in ambient air. Therefore, it is one of the 12 air pollutants with ...monitoring and assessment obligations set by the European Union Ambient Air Quality Directives. With low CO concentrations in Finland, continuous surface measurements are not compulsory but the monitoring and assessment obligation remains. Currently, there are no air quality stations equipped with CO measurements in Finland, and the assessment can only be based on emission estimates.
In this work, we demonstrate the use of satellite-based CO measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on-board Sentinel-5 Precursor satellite (S5P) to strengthen the assessment with actual measurements. Averaging satellite measurements over several years reveals the spatial distribution of CO with nationwide coverage in city-scale resolution. Individual satellite measurements, in turn, are used to estimate the surface concentrations and their annual variability in different regions in Finland.
For the surface estimates, we used a simple and robust linear model between the satellite measurements and ground-level in-situ measurements. We found that the linear model produces reasonable surface concentration estimates to be used in air quality assessments where the objective is to evaluate whether the monitoring threshold set by the EU is exceeded on a yearly scale. It is noted that cloudiness can cause local data gaps of several days and the low solar elevation angles prevent satellite measurements from 9 to 18 weeks during the winter time in Finland.
In Finland, the average total columns show low spatial variability, with only a few high-concentration areas identified. For the last three years, the estimated surface concentrations have stayed well below the lower assessment threshold set by the Air Quality Directive.
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•Satellite observations improve spatial coverage for national air quality reporting.•Long-term averaging of satellite observations reveals spatial distribution of CO in Finland.•Annual mean and maximum surface concentrations estimated from satellite measurements.•Satellite-based estimates are especially useful in areas with sparse monitoring network.
Observations taken over the last few decades indicate that dramatic changes are occurring in the ArcticBoreal Zone (ABZ), which are having significant impacts on ABZ inhabitants, infrastructure, ...flora and fauna, and economies. While suitable for detecting overall change, the current capability is inadequate for systematic monitoring and for improving process based and large scale understanding of the integrated components of the ABZ, which includes the cryosphere, biosphere, hydrosphere, and atmosphere. Such knowledge will lead to improvements in Earth system models, enabling more accurate prediction of future changes and development of informed adaptation and mitigation strategies. In this article, we review the strengths and limitations of current space based observational capabilities for several important ABZ components and make recommendations for improving upon these current capabilities. We recommend an interdisciplinary and stepwise approach to develop a comprehensive ABZ Observing Network (ABZON), beginning with an initial focus on observing networks designed to gain process based understanding for individual ABZ components and systems that can then serve as the building blocks for a comprehensive ABZON.
Recent advances in satellite observations of methane provide increased opportunities for inverse modeling. However, challenges exist in the satellite observation optimization and retrievals for high ...latitudes. In this study, we examine possibilities and challenges in the use of the total column averaged dry-air mole fractions of methane (XCHsub.4) data over land from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor satellite in the estimation of CHsub.4 fluxes using the CarbonTracker Europe-CHsub.4 (CTE-CHsub.4) atmospheric inverse model. We carry out simulations assimilating two retrieval products: Netherlands Institute for Space Research's (SRON) operational and University of Bremen's Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). For comparison, we also carry out a simulation assimilating the ground-based surface data. Our results show smaller regional emissions in the TROPOMI inversions compared to the prior and surface inversion, although they are roughly within the range of the previous studies. The wetland emissions in summer and anthropogenic emissions in spring are lesser. The inversion results based on the two satellite datasets show many similarities in terms of spatial distribution and time series but also clear differences, especially in Canada, where CHsub.4 emission maximum is later, when the SRON's operational data are assimilated. The TROPOMI inversions show higher CHsub.4 emissions from oil and gas production and coal mining from Russia and Kazakhstan. The location of hotspots in the TROPOMI inversions did not change compared to the prior, but all inversions indicated spatially more homogeneous high wetland emissions in northern Fennoscandia. In addition, we find that the regional monthly wetland emissions in the TROPOMI inversions do not correlate with the anthropogenic emissions as strongly as those in the surface inversion. The uncertainty estimates in the TROPOMI inversions are more homogeneous in space, and the regional uncertainties are comparable to the surface inversion. This indicates the potential of the TROPOMI data to better separately estimate wetland and anthropogenic emissions, as well as constrain spatial distributions. This study emphasizes the importance of quantifying and taking into account the model and retrieval uncertainties in regional levels in order to improve and derive more robust emission estimates.
In this paper, we propose improved nitrogen dioxide (NO2) to nitrogen oxide (NOx) scaling factors for several data-driven methods that are used for the estimation of NOx power plant emissions from ...satellite observations of NO2. The scaling factors are deduced from high-resolution simulations of power plant plumes with the MicroHH large-eddy simulation model with a simplified chemistry and then applied to Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) NO2 satellite observations over the Matimba/Medupi power stations in South Africa. We show that due to the non-linear chemistry the optimal NO2 to NOx scaling factors depend on both the method employed and the specific segments of the plume from which emission estimate is derived. The scaling factors derived from the MicroHH simulations in this study are substantially (more than 50%) higher than the typical values used in the literature with actual NO2 observations. The results highlight the challenge in appropriately accounting for the conversion from NO2 to NOx when estimating point source emissions from satellite NO2 observations.
•NO2 to NOx scaling factors calculated from the MicroHH large-eddy simulations.•Optimal scaling factors depend on the emission inversion method.•Scaling factors applied to derive NOx emissions from S5P/TROPOMI NO2 observations.•Optimal scaling factors are substantially higher than the values previously used.
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![CH[sub.4] Fluxes Derived fr...](http://api.summon.serialssolutions.com/2.0.0/image/issn/XR4PS5YY4K/2072-4292/small "CH[sub.4] Fluxes Derived from Assimilation of TROPOMI XCH[sub.4] in CarbonTracker Europe-CH[sub.4]: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes")