In support of the first Tropospheric Ozone Assessment Report (TOAR) a relational database of global surface ozone observations has been developed and populated with hourly measurement data and enhanced metadata. A comprehensive suite of ozone data products including standard statistics, health and vegetation impact metrics, and trend information, are made available through a common data portal and a web interface. These data form the basis of the TOAR analyses focusing on human health, vegetation, and climate relevant ozone issues, which are part of this special feature.Cooperation among many data centers and individual researchers worldwide made it possible to build the world's largest collection of in-situ hourly surface ozone data covering the period from 1970 to 2015. By combining the data from almost 10,000 measurement sites around the world with global metadata information, new analyses of surface ozone have become possible, such as the first globally consistent characterisations of measurement sites as either urban or rural/remote. Exploitation of these global metadata allows for new insights into the global distribution, and seasonal and long-term changes of tropospheric ozone and they enable TOAR to perform the first, globally consistent analysis of present-day ozone concentrations and recent ozone changes with relevance to health, agriculture, and climate.Considerable effort was made to harmonize and synthesize data formats and metadata information from various networks and individual data submissions. Extensive quality control was applied to identify questionable and erroneous data, including changes in apparent instrument offsets or calibrations. Such data were excluded from TOAR data products. Limitations of a posteriori data quality assurance are discussed. As a result of the work presented here, global coverage of surface ozone data for scientific analysis has been significantly extended. Yet, large gaps remain in the surface observation network both in Schultz et al: Tropospheric Ozone Assessment Report Art. 58, page 2 of 26 terms of regions without monitoring, and in terms of regions that have monitoring programs but no public access to the data archive. Therefore future improvements to the database will require not only improved data harmonization, but also expanded data sharing and increased monitoring in data-sparse regions.
Abstract. This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.
Abstract. We present intercomparison results for formaldehyde (HCHO) slant column measurements performed during the Cabauw Intercomparison campaign of Nitrogen Dioxide measuring Instruments (CINDI) that took place in Cabauw, the Netherlands, in summer 2009. During two months, nine atmospheric research groups simultaneously operated MAX-DOAS (MultiAXis Differential Optical Absorption Spectroscopy) instruments of various designs to record UV-visible spectra of scattered sunlight at different elevation angles that were analysed using common retrieval settings. The resulting HCHO data set was found to be highly consistent, the mean difference between instruments generally not exceeding 15% or 7.5 × 1015 molec cm−2, for all viewing elevation angles. Furthermore, a sensitivity analysis was performed to investigate the uncertainties in the HCHO slant column retrieval when varying key input parameters such as the molecular absorption cross sections, correction terms for the Ring effect or the width and position of the fitting interval. This study led to the identification of potentially important sources of errors associated with cross-correlation effects involving the Ring effect, O4, HCHO and BrO cross sections and the DOAS closure polynomial. As a result, a set of updated recommendations was formulated for HCHO slant column retrieval in the 336.5–359 nm wavelength range. To conclude, an error budget is proposed which distinguishes between systematic and random uncertainties. The total systematic error is estimated to be of the order of 20% and is dominated by uncertainties in absorption cross sections and related spectral cross-correlation effects. For a typical integration time of one minute, random uncertainties range between 5 and 30%, depending on the noise level of individual instruments.
Published by Copernicus Publications on behalf of the European Geosciences Union. 458 A. J. M. Piters et al.: The CINDI campaign: design, execution and early resultsAbstract. From June to July 2009 more than thirty different in-situ and remote sensing instruments from all over the world participated in the Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI). The campaign took place at KNMI's Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Its main objectives were to determine the accuracy of state-ofthe-art ground-based measurement techniques for the detection of atmospheric nitrogen dioxide (both in-situ and remote sensing), and to investigate their usability in satellite data validation. The expected outcomes are recommendations regarding the operation and calibration of such instruments, retrieval settings, and observation strategies for the use in ground-based networks for air quality monitoring and satellite data validation. Twenty-four optical spectrometers participated in the campaign, of which twenty-one had the capability to scan different elevation angles consecutively, the so-called Multi-axis DOAS systems, thereby collecting vertical profile information, in particular for nitrogen dioxide and aerosol. Various in-situ samplers and lidar instruments simultaneously characterized the variability of atmospheric trace gases and the physical properties of aerosol particles. A large data set of continuous measurements of these atmospheric constituents has been collected under various meteorological conditions and air pollution levels. Together with the permanent measurement capability at the CE-SAR site characterizing the meteorological state of the atmosphere, the CINDI campaign provided a comprehensive observational data set of atmospheric constituents in a highly polluted region of the world during summertime. First detailed comparisons performed with the CINDI data show that slant column measurements of NO 2 , O 4 and HCHO with MAX-DOAS agree within 5 to 15 %, vertical profiles of NO 2 derived from several independent instruments agree within 25 % of one another, and MAX-DOAS aerosol optical thickness agrees within 20-30 % with AERONET data. For the in-situ NO 2 instrument using a molybdenum converter, a bias was found as large as 5 ppbv during day time, when compared to the other in-situ instruments using photolytic converters.
Abstract. Iodine monoxide (IO) differential slant column densities (DSCD) have been retrieved from a new multi-axis differential optical absorption spectroscopy (MAX-DOAS) instrument deployed at the Izaña subtropical observatory as part of the Network for the Detection of Atmospheric Composition Change (NDACC) programme. The station is located at 2370 m a.s.l., well above the trade wind inversion that limits the top of the marine boundary layer, and hence is representative of the free troposphere. We report daily observations from May to August 2010 at different viewing angles. During this period, the spectral signature of IO was unequivocally detected on every day of measurement. A mean IO DSCD of 1.52×10 13 molecules cm −2 was observed at the 5 • instrument elevation angle (IEA) on clear days using a single zenith reference for the reported period, with a day-to-day variability of 33 % at one standard deviation. Based on the simulation of the DSCDs using radiative transfer calculations with five different hypothesized IO profiles, the IO mixing ratio is estimated to range between 0.2 and 0.4 pptv in the free troposphere. Episodes of Saharan dust outbreaks were also observed, with large increases in the DSCDs at higher IEA, suggesting an enhancement of IO inside the dust cloud.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.