The Unmanned Systems Research Laboratory (USRL) of the Cyprus Institute is a new mobile exploratory platform of the EU Research Infrastructure Aerosol, Clouds and Trace Gases Research InfraStructure (ACTRIS). USRL offers exclusive Unmanned Aerial Vehicle (UAV)-sensor solutions that can be deployed anywhere in Europe and beyond, e.g., during intensive field campaigns through a transnational access scheme in compliance with the drone regulation set by the European Union Aviation Safety Agency (EASA) for the research, innovation, and training. UAV sensor systems play a growing role in the portfolio of Earth observation systems. They can provide cost-effective, spatial in-situ atmospheric observations which are complementary to stationary observation networks. They also have strong potential for calibrating and validating remote-sensing sensors and retrieval algorithms, mapping close-to-the-ground emission point sources and dispersion plumes, and evaluating the performance of atmospheric models. They can provide unique information relevant to the short- and long-range transport of gas and aerosol pollutants, radiative forcing, cloud properties, emission factors and a variety of atmospheric parameters. Since its establishment in 2015, USRL is participating in major international research projects dedicated to (1) the better understanding of aerosol-cloud interactions, (2) the profiling of aerosol optical properties in different atmospheric environments, (3) the vertical distribution of air pollutants in and above the planetary boundary layer, (4) the validation of Aeolus satellite dust products by utilizing novel UAV-balloon-sensor systems, and (5) the chemical characterization of ship and stack emissions. A comprehensive overview of the new UAV-sensor systems developed by USRL and their field deployments is presented here. This paper aims to illustrate the strong scientific potential of UAV-borne measurements in the atmospheric sciences and the need for their integration in Earth observation networks.

Ocean-emitted dimethyl sulfide (DMS) is a major source of climate-cooling aerosols. However, most of the marine biogenic sulfur cycling is not routed to DMS but to methanethiol (MeSH), another volatile whose reactivity has hitherto hampered measurements. Therefore, the global emissions and climate impact of MeSH remain unexplored. We compiled a database of seawater MeSH concentrations, identified their statistical predictors, and produced monthly fields of global marine MeSH emissions adding to DMS emissions. Implemented into a global chemistry-climate model, MeSH emissions increase the sulfate aerosol burden by 30 to 70% over the Southern Ocean and enhance the aerosol cooling effect while depleting atmospheric oxidants and increasing DMS lifetime and transport. Accounting for MeSH emissions reduces the radiative bias of current climate models in this climatically relevant region.

The Oxygenated Compounds in the Tropical Atmosphere: Variability and Exchanges (OCTAVE) campaign aimed to improve the assessment of the budget and role of oxygenated volatile organic compounds (OVOCs) in tropical regions, and especially over oceans, relying on an integrated approach combining in situ measurements, satellite retrievals, and modeling. As part of OCTAVE, volatile organic compounds (VOCs) were measured using a comprehensive suite of instruments on Reunion Island (21.07° S, 55.38° E) from 7 March to 2 May 2018. VOCs were measured at a receptor site at the Maïdo observatory during the entire campaign and at two source sites: Le Port from 19 to 24 April 2018 (source of anthropogenic emissions) and Bélouve from 25 April to 2 May 2018 (source of biogenic emissions) within a mobile lab. The Maïdo observatory is a remote background site located at an altitude of 2200 m, whereas Bélouve is located in a tropical forest to the east of Maïdo and Le Port is an urban area located northwest of Maïdo. The major objective of this study was to understand the sources and distributions of atmospheric formaldehyde (HCHO) in the Maïdo observatory on Reunion Island. To address this objective, two different approaches were used to quantify and determine the main drivers of HCHO at Maïdo. First, a chemical-kinetics-based (CKB) calculation method was used to determine the sources and sinks (biogenic, anthropogenic/primary, or secondary) of HCHO at the Maïdo site. The CKB method shows that 9% of the formaldehyde formed from biogenic emissions and 89% of HCHO had an unknown source; that is, the sources cannot be explicitly described by this method. Next, a positive matrix factorization (PMF) model was applied to characterize the VOC source contributions at Maïdo. The PMF analysis including VOCs measured at the Maïdo observatory shows that the most robust solution was obtained with five factors: secondary biogenic accounting for 17%, primary anthropogenic/solvents (24%), primary biogenic (14%), primary anthropogenic/combustion (22%), and background (23%). The main contributions to formaldehyde sources as described by the PMF model are secondary biogenic (oxidation of biogenic VOCs with 37%) and background (32%). Some assumptions were necessary concerning the high percentage of unknown HCHO sources of the CKB calculation method such as the biogenic emission factor resulting in large discrepancies between the two methods.

The real-time monitoring of primary biological aerosol particles (PBAP) such as pollen and fungal spores has received much attention in recent years as a result of their health and climatic effects. In this study, the Wideband Integrated Bioaerosol Sensor (WIBS) 4+ model was evaluated for its ability to sample and detect ambient fungal spore and pollen concentrations, compared to the traditional Hirst volumetric method. Although the determination of total pollen and fungal spore ambient concentrations are of interest, the selective detection of individual pollen/fungal spore types are often of greater allergenic/agricultural concern. To aid in this endeavour, modifications were made to the WIBS-4 instrument to target chlorophyll fluorescence. Two additional fluorescence channels (FL4 and FL5 channels) were combined with the standard WIBS channels (FL1, FL2, FL3). The purpose of this modification is to help discriminate between grass and herb pollen from other pollen. The WIBS-4+ was able to successfully detect and differentiate between different bioaerosol classes. The addition of the FL4 and FL5 channels also allowed for the improved differentiation between tree (R² = 0.8), herbaceous (R² = 0.6) and grass (R² = 0.4) pollen and fungal spores (R² = 0.8). Both grass and herbaceous pollen types showed a high correlation with D type particles, showing strong fluorescence in the FL4 channel. The additional fluorescent data that were introduced also improved clustering attempts, making k-means clustering a comparable solution for this high-resolution data.

Airborne fungal spores (AFS) represent the major fraction of primary biological aerosol particles (PBAPs), and they are studied worldwide largely due to their important role within the Earth system. They have an impact on climate and human health, and they contribute to the propagation of diseases. As their presence in the air depends largely on studied ecosystems, a spore trap was used to monitor their atmospheric concentrations from 2014 to December 2018 in Saclay, a suburban area in the megacity of Paris. The main objective of this work was: (1) to understand the atmospheric variability of AFS in relation to different variables such as meteorological factors, agricultural practice, and (2) to identify their geographical origin by using a source receptor model. During our period of observation, 30 taxa have been identified under a light microscope. In order of importance, Ascospores, Cladosporium, Basidiospores, Tilletiopsis, Alternaria were found to be the most abundant types respectively (50.8%, 33.6%, 7.6%, 1.8%, and 1.3%) accounting for 95% of the atmospheric concentrations. We observed a general decrease associated with a strong interannual variability. A bimodal seasonal cycle was identified with a first maximum in July and a second in October. The main parameters driving the atmospheric concentration are temperature and precipitation. The daily variability is strongly activated by successive periods of hot weather and rainfall, multiplying the concentration by a factor of 1000 in less than 12 hours. Results from the source receptor model ZeFir point out unambiguous different origins of AFS due to specific sources impacting the observation site. Our study also indicated that a hydrological stress has a direct effect on the daily concentrations. This last point should be taken into account for every stressed ecosystem studied in a global warming context. This is particularly important for Mediterranean areas where water is a key control of the growth and dispersion of fungal spores.

Measurements of primary biological aerosol particles (PBAPs) have been conducted worldwide using ultraviolet light-induced fluorescence (UV-LIF) spectrometers. However, how these instruments detect and respond to known biological and non-biological particles, and how they compare, remains uncertain due to limited laboratory intercomparisons. Using the Defence Science and Technology Laboratory, Aerosol Challenge Simulator (ACS), controlled concentrations of biological and non-biological aerosol particles, singly or as mixtures, were produced for testing and intercomparison of multiple versions of the Wideband Integrated Bioaerosol Spectrometer (WIBS) and Multiparameter Bioaerosol Spectrometer (MBS). Although the results suggest some challenges in discriminating biological particle types across different versions of the same UV-LIF instrument, a difference in fluorescence intensity between the non-biological and biological samples could be identified for most instruments. While lower concentrations of fluorescent particles were detected by the MBS, the MBS demonstrates the potential to discriminate between pollen and other biological particles. This study presents the first published technical summary and use of the ACS for instrument intercomparisons. Within this work a clear overview of the data pre-processing is also presented, and documentation of instrument version/model numbers is suggested to assess potential instrument variations between different versions of the same instrument. Further laboratory studies sampling different particle types are suggested before use in quantifying impact on ambient classification.