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Ground-based observations of 11.072 GHz atmospheric ozone (O3) emission have been made using the Ny-Ålesund Ozone in the Mesosphere Instrument (NAOMI) at the UK Arctic Research Station (latitude 78∘55′0′′ N, longitude 11∘55′59′′ E), Spitsbergen. Seasonally averaged O3 vertical profiles in the Arctic polar mesosphere–lower thermosphere region for night-time and twilight conditions in the period 15 August 2017 to 15 March 2020 have been retrieved over the altitude range 62–98 km. NAOMI measurements are compared with corresponding, overlapping observations by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) satellite instrument. The NAOMI and SABER version 2.0 data are binned according to the SABER instrument 60 d yaw cycles into nominal 3-month “winter” (15 December–15 March), “autumn” (15 August–15 November), and “summer” (15 April–15 July) periods. The NAOMI observations show the same year-to-year and seasonal variabilities as the SABER 9.6 µm O3 data. The winter night-time (solar zenith angle, SZA ≥ 110∘) and twilight (75∘ ≤ SZA ≤ 110∘) NAOMI and SABER 9.6 µm O3 volume mixing ratio (VMR) profiles agree to within the measurement uncertainties. However, for autumn twilight conditions the SABER 9.6 µm O3 secondary maximum VMR values are higher than NAOMI over altitudes 88–97 km by 47 % and 59 %, respectively in 2017 and 2018. Comparing the two SABER channels which measure O3 at different wavelengths and use different processing schemes, the 9.6 µm O3 autumn twilight VMR data for the three years 2017–2019 are higher than the corresponding 1.27 µm measurements with the largest difference (58 %) in the 65–95 km altitude range similar to the NAOMI observation. The SABER 9.6 µm O3 summer daytime (SZA < 75∘) mesospheric O3 VMR is also consistently higher than the 1.27 µm measurement, confirming previously reported differences between the SABER 9.6 µm channel and measurements of mesospheric O3 by other satellite instruments.

The SPectrometer for Ice Nuclei (SPIN) is a commercially available ice nucleating particle (INP) counter manufactured by Droplet Measurement Technologies in Boulder, CO. The SPIN is a continuous flow diffusion chamber with parallel plate geometry based on the Zurich Ice Nucleation Chamber and the Portable Ice Nucleation Chamber. This study presents a standard description for using the SPIN instrument and also highlights methods to analyze measurements in more advanced ways. It characterizes and describes the behavior of the SPIN chamber, reports data from laboratory measurements, and quantifies uncertainties associated with the measurements. Experiments with ammonium sulfate are used to investigate homogeneous freezing of deliquesced haze droplets and droplet breakthrough. Experiments with kaolinite, NX illite, and silver iodide are used to investigate heterogeneous ice nucleation. SPIN nucleation results are compared to those from the literature. A machine learning approach for analyzing depolarization data from the SPIN optical particle counter is also presented (as an advanced use). Overall, we report that the SPIN is able to reproduce previous INP counter measurements. Atmospheric Measurement Techniques, 9 (7) ISSN:1867-8548 ISSN:1867-1381

Abstract. An important problem in satellite remote sensing of aerosols is related to the need to perform an adequate cloud screening. If a cloud screening is applied that is not strict enough, the ground scene has the probability of residual cloud cover which causes large errors on the retrieved aerosol parameters. On the other hand, if the cloud-screening procedure is too strict, too many clear sky cases, especially near-cloud scenes, will falsely be flagged cloudy. The detrimental effects of cloud contamination as well as the importance of aerosol cloud interactions that can be studied in these near-cloud scenes call for new approaches to cloud screening. Multi-angle multi-wavelength photopolarimetric measurements have a unique capability to distinguish between scattering by (liquid) cloud droplets and aerosol particles. In this paper the sensitivity of aerosol retrievals from multi-angle photopolarimetric measurements to cloud contamination is investigated and the ability to intrinsically filter the cloud-contaminated scenes based on a goodness-of-fit criteria is evaluated. Hereto, an aerosol retrieval algorithm is applied to a partially clouded over-ocean synthetic data set as well as non-cloud-screened over-ocean POLDER-3/PARASOL observations. It is found that a goodness-of-fit filter, together with a filter on the coarse mode refractive index (mrcoarse > 1.335) and a cirrus screening, adequately rejects the cloud-contaminated scenes. No bias or larger SD are found in the retrieved parameters for this intrinsic cloud filter compared to the parameters retrieved in a priori cloud-screened data set (using MODIS/AQUA cloud masks) of PARASOL observations. Moreover, less high-aerosol load scenes are misinterpreted as cloud contaminated. The retrieved aerosol optical thickness, single scattering albedo and Ångström exponent show good agreement with AERONET observations. Furthermore, the synthetic retrievals give confidence in the ability of the algorithm to correctly retrieve the micro-physical aerosol parameters.

The Airborne imaging differential optical absorption spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP) has been developed for the purpose of trace gas measurements and pollution mapping. The instrument has been characterized and successfully operated from aircraft. Nitrogen dioxide (NO2) columns were retrieved from the AirMAP observations. A major benefit of the push-broom imaging instrument is the spatially continuous, gap-free measurement sequence independent of flight altitude, a valuable characteristic for mapping purposes. This is made possible by the use of a charge coupled device (CCD) frame-transfer detector. A broad field of view across track of around 48° is achieved with wide-angle entrance optics. This leads to a swath width of about the same size as the flight altitude. The use of fibre coupled light intake optics with sorted light fibres allows flexible instrument positioning within the aircraft and retains the very good imaging capabilities. The measurements yield ground spatial resolutions below 100 m depending on flight altitude. The number of viewing directions is chosen from a maximum of 35 individual viewing directions (lines of sight, LOS) represented by 35 individual fibres. The selection is adapted to each situation by averaging according to signal-to-noise or spatial resolution requirements. Observations at 30 m spatial resolution are obtained when flying at 1000 m altitude and making use of all 35 viewing directions. This makes the instrument a suitable tool for mapping trace gas point sources and small-scale variability. The position and aircraft attitude are taken into account for accurate spatial mapping using the Attitude and Heading Reference System of the aircraft. A first demonstration mission using AirMAP was undertaken in June 2011. AirMAP was operated on the AWI Polar-5 aircraft in the framework of the AIRMETH-2011 campaign. During a flight above a medium-sized coal-fired power plant in north-west Germany, AirMAP clearly detected the emission plume downwind from the exhaust stack, with NO2 vertical columns around 2 × 1016 molecules cm−2 in the plume centre. NOx emissions estimated from the AirMAP observations are consistent with reports in the European Pollutant Release and Transfer Register. Strong spatial gradients and variability in NO2 amounts across and along flight direction are observed, and small-scale enhancements of NO2 above a motorway are detected.

A method for directly measuring carbon dioxide (CO2) emissions using a mobile sensor network in cities at fine spatial resolution was developed and tested. First, a compact, mobile system was built using an infrared gas analyzer combined with open-source hardware to control, georeference, and log measurements of CO2 mixing ratios on vehicles (car, bicycles). Second, two measurement campaigns, one in summer and one in winter (heating season) were carried out. Five mobile sensors were deployed within a 1 × 12. 7 km transect across the city of Vancouver, BC, Canada. The sensors were operated for 3.5 h on pre-defined routes to map CO2 mixing ratios at street level, which were then averaged to 100 × 100 m grid cells. The averaged CO2 mixing ratios of all grids in the study area were 417.9 ppm in summer and 442.5 ppm in winter. In both campaigns, mixing ratios were highest in the grid cells of the downtown core and along arterial roads and lowest in parks and well vegetated residential areas. Third, an aerodynamic resistance approach to calculating emissions was used to derive CO2 emissions from the gridded CO2 mixing ratio measurements in conjunction with mixing ratios and fluxes collected from a 28 m tall eddy-covariance tower located within the study area. These measured emissions showed a range of −12 to 226 CO2 ha−1 h−1 in summer and of −14 to 163 kg CO2 ha−1 h−1 in winter, with an average of 35.1 kg CO2 ha−1 h−1 (summer) and 25.9 kg CO2 ha−1 h−1 (winter). Fourth, an independent emissions inventory was developed for the study area using buildings energy simulations from a previous study and routinely available traffic counts. The emissions inventory for the same area averaged to 22.06 kg CO2 ha−1 h−1 (summer) and 28.76 kg CO2 ha−1 h−1 (winter) and was used to compare against the measured emissions from the mobile sensor network. The comparison on a grid-by-grid basis showed linearity between CO2 mixing ratios and the emissions inventory (R2 = 0. 53 in summer and R2 = 0. 47 in winter). Also, 87 % (summer) and 94 % (winter) of measured grid cells show a difference within ±1 order of magnitude, and 49 % (summer) and 69 % (winter) show an error of less than a factor 2. Although associated with considerable errors at the individual grid cell level, the study demonstrates a promising method of using a network of mobile sensors and an aerodynamic resistance approach to rapidly map greenhouse gases at high spatial resolution across cities. The method could be improved by longer measurements and a refined calculation of the aerodynamic resistance.

Low concentrations of ice-nucleating particles (INPs) are thought to be important for the properties of mixed-phase clouds, but their detection is challenging. Hence, there is a need for instruments where INP concentrations of less than 0.01 L−1 can be routinely and efficiently determined. The use of larger volumes of suspension in drop assays increases the sensitivity of an experiment to rarer INPs or rarer active sites due to the increase in aerosol or surface area of particulates per droplet. Here we describe and characterise the InfraRed-Nucleation by Immersed Particles Instrument (IR-NIPI), a new immersion freezing assay that makes use of IR emissions to determine the freezing temperature of individual 50 µL droplets each contained in a well of a 96-well plate. Using an IR camera allows the temperature of individual aliquots to be monitored. Freezing temperatures are determined by detecting the sharp rise in well temperature associated with the release of heat caused by freezing. In this paper we first present the calibration of the IR temperature measurement, which makes use of the fact that following ice nucleation aliquots of water warm to the ice–liquid equilibrium temperature (i.e. 0 ∘C when water activity is ∼1), which provides a point of calibration for each individual well in each experiment. We then tested the temperature calibration using ∼100 µm chips of K-feldspar, by immersing these chips in 1 µL droplets on an established cold stage (µL-NIPI) as well as in 50 µL droplets on IR-NIPI; the results were consistent with one another, indicating no bias in the reported freezing temperature. In addition we present measurements of the efficiency of the mineral dust NX-illite and a sample of atmospheric aerosol collected on a filter in the city of Leeds. NX-illite results are consistent with literature data, and the atmospheric INP concentrations were in good agreement with the results from the µL-NIPI instrument. This demonstrates the utility of this approach, which offers a relatively high throughput of sample analysis and access to low INP concentrations.

Abstract. The ozone profile records of a large number of limb and occultation satellite instruments are widely used to address several key questions in ozone research. Further progress in some domains depends on a more detailed understanding of these data sets, especially of their long-term stability and their mutual consistency. To this end, we made a systematic assessment of 14 limb and occultation sounders that, together, provide more than three decades of global ozone profile measurements. In particular, we considered the latest operational Level-2 records by SAGE II, SAGE III, HALOE, UARS MLS, Aura MLS, POAM II, POAM III, OSIRIS, SMR, GOMOS, MIPAS, SCIAMACHY, ACE-FTS and MAESTRO. Central to our work is a consistent and robust analysis of the comparisons against the ground-based ozonesonde and stratospheric ozone lidar networks. It allowed us to investigate, from the troposphere up to the stratopause, the following main aspects of satellite data quality: long-term stability, overall bias and short-term variability, together with their dependence on geophysical parameters and profile representation. In addition, it permitted us to quantify the overall consistency between the ozone profilers. Generally, we found that between 20 and 40 km the satellite ozone measurement biases are smaller than ±5 %, the short-term variabilities are less than 5–12 % and the drifts are at most ±5 % decade−1 (or even ±3 % decade−1 for a few records). The agreement with ground-based data degrades somewhat towards the stratopause and especially towards the tropopause where natural variability and low ozone abundances impede a more precise analysis. In part of the stratosphere a few records deviate from the preceding general conclusions; we identified biases of 10 % and more (POAM II and SCIAMACHY), markedly higher single-profile variability (SMR and SCIAMACHY) and significant long-term drifts (SCIAMACHY, OSIRIS, HALOE and possibly GOMOS and SMR as well). Furthermore, we reflected on the repercussions of our findings for the construction, analysis and interpretation of merged data records. Most notably, the discrepancies between several recent ozone profile trend assessments can be mostly explained by instrumental drift. This clearly demonstrates the need for systematic comprehensive multi-instrument comparison analyses.