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:In this study we present the UK's total ozone and UV data records, their measurement and preliminary processing, and discuss the observed trends. Notably, we combine the records from the Camborne and Reading sites to obtain a single ozone data series for southern England -a total duration of 30 years.Two-section linear trends and cross-over years are determined for Lerwick and southern England, both annually and seasonally. The observed minimum using this technique in the UK ozone record is found to occur during the year 1993. Significant trends of −4.8% per decade for southern England and −5.8% per decade for Lerwick are seen prior to the mid-1990s; the rate of decrease in the UK being at the upper limit of other European stations. No significant ozone trend is seen for the latter period in either location in contrast with Europe as a whole. We, additionally, compare the satellite-derived total ozone trends for both locations.The UV record at Reading showed a significant trend from 1993 to 2008 in the daily maximum UV index record (6.6% per decade), despite no significant recovery in the total ozone data series, suggesting a reduction in cloud cover during the midday period. Filtering data to remove other factors shows the erythemal UV to have an ozone-dependent trend of −0.11% per year, but this is not statistically significant. We find no correlation between anomalies in the surface UV and total ozone records suggesting that the majority of the inter-annual variability is due to changes in cloud cover and other effects.

Abstract. This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument 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 DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 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 an 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 bias for the stratospheric column data, of about −0.2 Pmolec/cm2, 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/cm2 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/cm2), but exceed those for the tropospheric column data (0.7 Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, 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 chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2 Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (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.

We have used anodization techniques to process porous surface regions in p-type Czochralski Si and in p-type Sio,ssGe,-,,s p e itaxial layers grown by molecular beam epitaxy. The SiGe layers were unrelaxed before processing. We have observed strong near-infrared and visible light emission from both systems. Analysis of the radiative and nonradiative recombination processes indicate that the emission is consistent with the decay of excitons localized in structures of one or zero dimensions.

A detailed map of the available UV across the UK from 2003 to 2012 is provided. A suite of data derived from climatologies and satellite observations are used to calculate spectral UV irradiance and related weighted doses (erythema, DNA damage, vitamin D). The result is a well-validated tool that has two advantages: (i) the output is simulated spectral UV irradiance that can be weighted with any action spectrum for use in any research studies that require ambient UV data, (ii) reliance on instruments with planned operational lives of at least several years that ensures data and method homogeneity for extension to future studies. The model-derived doses are satisfactory validated against spectral ground-based measurements at two sites. According to the calculated climatology, the southern part of the UK receives 1.5-2 times more UV than the north during spring, summer and autumn. During wintertime, the UV doses in the far north are an order of magnitude lower than southern values. Even for the same latitude, regional variations of cloudiness result in doses at coastal sites being up to 25% higher than inland areas.