We demonstrate a novel approach to estimating emissions from oil sands operations that utilizes the GreenLITE™ gas concentration measurement system and an atmospheric model. While deployed at a facility in the Athabasca region of Alberta, Canada, CH₄ emissions from a tailings pond were estimated to be 7.2 t/d for July–October 2019, and 5.1 t/d for March–July 2020. CH₄ emissions from an open-pit mine were estimated to be 24.6 t/d for September–October 2019.

The relationship between the non-volatile particulate matter (nvPM) mass emissions produced by different engine sources and the response of the LII 300 instrument, used for regulatory measurements of nvPM mass emissions in aircraft engine certification tests, was investigated for different sources and operating conditions. Laser fluence optimisation was required for real-time nvPM mass concentration measurements. These results will inform the development of updated calibration protocols.

Weather radar data are used in weather monitoring and forecasting, but they are affected by numerous errors and require advanced corrections. Different systems are designed and implemented to suit specific local conditions, like the RADVOL-QC system. The radar errors are divided into several groups: disturbance by non-meteorological echoes (from the mountains, RLAN signals, wind turbines, etc.), beam blockage, attenuation, etc. Each of them has different properties and is corrected differently.

It is important to detect the vertical distribution of cloud droplets and ice in mixed-phase clouds. Here, an artificial neural network (ANN) previously developed for Arctic clouds is applied to a mid-latitudinal cloud radar data set. The performance of this technique is contrasted to the Cloudnet target classification. For thick/multi-layer clouds, the machine learning technique is better at detecting liquid than Cloudnet, but if lidar data are available Cloudnet is at least as good as the ANN.

We applied the air-mass-corrected differential optical absorption spectroscopy (AMC-DOAS) method to derive total column water vapour (TCWV) from Sentinel-5P measurements and compared it to independent data sets. The correlation coefficients of typically more than 0.9 and the small deviations up to 2.5 kg m⁻² reveal good agreement between our data product and other TCWV data sets. In particular for the different Sentinel-5P water vapour products, the deviations are around 1 kg m⁻².

We present more than 2 years of NO₂ pollution measurements from a sensor network in Greater London and compare results to an extensive network of expensive reference-grade monitors. We show the ability of our lower-cost network to generate robust insights about local air pollution. We also show how irregularities in sensor performance lead to some uncertainty in results and demonstrate ways that future users can characterize and mitigate uncertainties to get the most value from sensor data.

The paper aims to use large-eddy simulations of cumulus clouds to design a sampling strategy that allows following cumulus clouds with remotely piloted aircraft (RPA) and documenting the cloud spatial heterogeneities. Different possible explorations by RPA are investigated, and the use of Gaussian process regression permits the reconstruction of liquid water content (LWC) distribution with only one RPA.

This paper describes an instrument that measures spectrally from 360 nm (ultraviolet) to 1070 nm (near-infrared) at 1002 separate wavelengths. The measurements were made every minute from the late summer of 2009 to the winter of 2014 at a site in northern Oklahoma (USA; 36.605° N, 97.486° W). Methods are described that enable the normalized transmission across the spectrum to be measured and, subsequently, used to calculate the aerosol optical depth and spectra irradiance.

We are using machine learning techniques, a type of artificial intelligence, to detect graupel formation in clouds. The measurements used as input to the machine learning framework were performed by cloud radars. Cloud radars are instruments located at the ground, emitting radiation with wavelenghts of a few millimeters vertically into the cloud and measuring the back-scattered signal. Our novel technique can be applied to different radar systems and different weather conditions.

Heating by solar radiation is the dominant error source for daytime temperature measurements by radiosondes. This paper describes a new laboratory setup (SISTER) to characterise this radiation error for pressures and ventilation speeds that are typical for the conditions between the surface and 35 km altitude. This characterisation is the basis for the radiation correction that is applied in the GRUAN data processing for the RS41 radiosonde. The GRUAN data product is compared to that of Vaisala.

An all-sky camera is used to obtain the relative sky radiance, and this radiance is used as input in an inversion code to obtain aerosol properties. This paper is really interesting because it pushes forward the use and capability of sky cameras for more advanced science purposes. Enhanced aerosol properties can be retrieved with accuracy using only an all-sky camera, but synergy with other instruments providing aerosol optical depth could even increase the power of these low-cost instruments.

Using data from the Infrared Atmospheric Sounding Interferometer (IASI) measurements of volcanic ash clouds (VACs) and radiative transfer calculations, we attempt to simulate the measured brightness temperature spectra (BTS) of volcanic ash aerosols in the infrared region. In particular, the dependence on the ash refractive index (RI) model is investigated.

Particle-phase nitrates are an important component of atmospheric aerosols and chemistry. In this paper, we systematically explore the application of aerosol mass spectrometry (AMS) to quantify the organic and inorganic nitrate fractions of aerosols in the atmosphere. While AMS has been used for a decade to quantify nitrates, methods are not standardized. We make recommendations for a more universal approach based on this analysis of a large range of field and laboratory observations.

The existing infrastructure for cellular communication is promising for ground-based rainfall remote sensing. Rain-induced signal attenuation is used in dedicated algorithms for retrieving rainfall depth along commercial microwave links (CMLs) between cell phone towers. This processing is a source of many uncertainties about input data, algorithm structures, parameters, CML network, and local climate. Application of a stochastic optimization method leads to improved CML rainfall estimates.

In this work, we review the use of quasi-vertical profiles for monitoring the calibration of the radar differential reflectivity Z_DR. We validate the proposed method by comparing its results against the traditional approach based on measurements taken at 90°; we observed good agreement as the errors are within 0.2 dB. Additionally, we compare the results of the proposed method with Z_DR derived from disdrometers; the errors are reasonable considering factors discussed in the paper.

In this paper we investigate the synergy obtained by combining active (radio acoustic sounding system – RASS) and passive (microwave radiometer) remote sensing observations to obtain temperature vertical profiles through a radiative transfer model. Inclusion of the RASS observations leads to more accurate temperature profiles from the surface to 5 km above ground, well above the maximum height of the RASS observations themselves (2000 m), when compared to the microwave radiometer used alone.

A comprehensive description and characterisation of the Manchester Aerosol Chamber (MAC) was conducted. The MAC has good temperature and relative humidity homogeneity, fast mixing times, and comparable losses of gases and particles with other chambers. The MAC's bespoke control system allows improved duty cycles and repeatable experiments. Moreover, the effect of contamination on performance was also investigated. It is highly recommended to regularly track the chamber's performance.

Soot particles with varying amounts of secondary organic matter coating were generated and used to compare a series of aerosol-absorption-measuring instruments: filter-based and photoacoustic instruments as well as photo-thermal interferometers. Significant deviations in the response of the instruments were observed depending on the amount of secondary organic coating. The system can be used for the inter-comparison and characterisation of instruments.