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The ambient atmospheric environment affects the growth and spread of wildland fires, whereas heat and moisture released from the fires and the reduction of the surface drag in the burned areas can significantly alter local atmospheric conditions. Observational studies on fire–atmosphere interactions have used instrumented towers to collect data during prescribed fires, but a few towers in an operational-scale burn plot (usually > 103 m2) have made it extremely challenging to capture the myriad of factors controlling fire–atmosphere interactions, many of which exhibit strong spatial variability. Here, we present analyses of atmospheric turbulence data collected using a 4 × 4 array of fast-response sonic anemometers during a fire experiment on a 10 m × 10 m burn plot. In addition to confirming some of the previous findings on atmospheric turbulence associated with low-intensity surface fires, our results revealed substantial heterogeneity in turbulent intensity and heat and momentum fluxes just above the combustion zone. Despite the small plot (100 m2), fire-induced atmospheric turbulence exhibited strong dependence on the downwind distance from the initial line fire and the relative position specific to the fire front as the surface fire spread through the burn plot. This result highlights the necessity for coupled atmosphere–fire behavior models to have 1–2 m grid spacing to resolve heterogeneities in fire–atmosphere interactions that operate on spatiotemporal scales relevant to atmospheric turbulence. The findings here have important implications for modeling smoke dispersion, as atmospheric dispersion characteristics in the vicinity of a wildland fire are directly affected by fire-induced turbulence.

Abstract Chimeric Antigen Receptor (CAR) T cells directed to B cell maturation antigen (BCMA) mediate profound responses in patients with multiple myeloma, but most patients do not achieve long-term complete remissions. In addition, recent evidence suggests that high-affinity binding to BCMA can result in on-target, off-tumor activity in the basal ganglia and can lead to fatal Parkinsonian-like disease. Here we develop CAR T cells against multiple myeloma using a binder to targeting transmembrane activator and CAML interactor (TACI) in mono and dual-specific formats with anti-BCMA. These CARs have robust, antigen-specific activity in vitro and in vivo. We also show that TACI RNA expression is limited in the basal ganglia, which may circumvent some of the toxicities recently reported with BCMA CARs. Thus, single-targeting TACI CARs may have a safer toxicity profile, whereas dual-specific BCMA-TACI CAR T cells have potential to avoid the antigen escape that can occur with single-antigen targeting.

Natural environmental change, anthropogenic development, and inter-annual variability can affect the ecology of estuarine fish and invertebrates. Yaquina Bay, Oregon, a well-studied estuary, has undergone intense development, as well as deep-draft dredging during the latter half of the 20th century, resulting in the alteration of ~45% of the lower estuary’s natural shoreline. In 1967, the United States Environmental Protection Agency (USEPA) conducted a 21-month survey of Yaquina Bay to characterize the demersal fishes and epibenthic crustaceans that occupy the bay. From 2003 to 2005, we conducted a 25-month survey to replicate that work and provide a comparative snapshot of the demersal fish and epibenthic crustacean community in the bay. A comparison of the trawl survey datasets reveals a 91% decline in total catch per unit effort (CPUE) between surveys, as well as a decline in multiple measures of biodiversity. Furthermore, the fishes and crustaceans of Yaquina Bay have experienced a shift in species dominance from demersal fishes in the late 1960s to epibenthic crustaceans in the 2000s, marked most notably by a nine-fold increase in the Dungeness crab CPUE. While this work does not establish a causal relationship between changes in the demersal communities of this West Coast estuary and human or natural events, it does document substantial changes in both the diversity and total abundance of animals in that community over a three-plus decade period of development and environmental variability. Hence, this forms a second baseline for continued long-term monitoring.

Clouds warm the surface in the longwave (LW), and this warming effect can be quantified through the surface LW cloud radiative effect (CRE). The global surface LW CRE has been estimated over more than 2 decades using space-based radiometers (2000–2021) and over the 5-year period ending in 2011 using the combination of radar, lidar and space-based radiometers. Previous work comparing these two types of retrievals has shown that the radiometer-based cloud amount has some bias over icy surfaces. Here we propose new estimates of the global surface LW CRE from space-based lidar observations over the 2008–2020 time period. We show from 1D atmospheric column radiative transfer calculations that surface LW CRE linearly decreases with increasing cloud altitude. These computations allow us to establish simple parameterizations between surface LW CRE and five cloud properties that are well observed by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) space-based lidar: opaque cloud cover and altitude and thin cloud cover, altitude, and emissivity. We evaluate this new surface LWCRE–LIDAR product by comparing it to existing satellite-derived products globally on instantaneous collocated data at footprint scale and on global averages as well as to ground-based observations at specific locations. This evaluation shows good correlations between this new product and other datasets. Our estimate appears to be an improvement over others as it appropriately captures the annual variability of the surface LW CRE over bright polar surfaces and it provides a dataset more than 13 years long.

Snowfall is the major source of mass for the Greenland ice sheet (GrIS) but the spatial and temporal variability of snowfall and the connections between snowfall and mass balance have so far been inadequately quantified. By characterizing local atmospheric circulation and utilizing CloudSat spaceborne radar observations of snowfall, we provide a detailed spatial analysis of snowfall variability and its relationship to Greenland mass balance, presenting first-of-their-kind maps of daily spatial variability in snowfall from observations across Greenland. For identified regional atmospheric circulation patterns, we show that the spatial distribution and net mass input of snowfall vary significantly with the position and strength of surface cyclones. Cyclones west of Greenland driving southerly flow contribute significantly more snowfall than any other circulation regime, with each daily occurrence of the most extreme southerly circulation pattern contributing an average of 1.66 Gt of snow to the Greenland ice sheet. While cyclones east of Greenland, patterns with the least snowfall, contribute as little as 0.58 Gt each day. Above 2 km on the ice sheet where snowfall is inconsistent, extreme southerly patterns are the most significant mass contributors, with up to 1.20 Gt of snowfall above this elevation. This analysis demonstrates that snowfall over the interior of Greenland varies by up to a factor of 5 depending on regional circulation conditions. Using independent observations of mass changes made by the Gravity Recovery and Climate Experiment (GRACE), we verify that the largest mass increases are tied to the southerly regime with cyclones west of Greenland. For occurrences of the strongest southerly pattern, GRACE indicates a net mass increase of 1.29 Gt in the ice sheet accumulation zone (above 2 km elevation) compared to the 1.20 Gt of snowfall observed by CloudSat. This overall agreement suggests that the analytical approach presented here can be used to directly quantify snowfall mass contributions and their most significant drivers spatially across the GrIS. While previous research has implicated this same southerly regime in ablation processes during summer, this paper shows that ablation mass loss in this circulation regime is nearly an order of magnitude larger than the mass gain from associated snowfall. For daily occurrences of the southerly circulation regime, a mass loss of approximately 11 Gt is observed across the ice sheet despite snowfall mass input exceeding 1 Gt. By analyzing the spatial variability of snowfall and mass changes, this research provides new insight into connections between regional atmospheric circulation and GrIS mass balance.

Understanding and quantifying land management impacts on local climate is important for distinguishing between the effects of land management and large-scale climate forcings. This study for the first time explicitly considers the radiative forcing resulting from realistic land management and offers new insights into the local land surface response to land management. Regression-based trend analysis is applied to observations and present-day ensemble simulations with the Community Earth System Model (CESM) version 1.2.2 to assess the impact of irrigation and conservation agriculture (CA) on warming trends using an approach that is less sensitive to temperature extremes. At the regional scale, an irrigation- and CA-induced acceleration of the annual mean near-surface air temperature (T2m) warming trends and the annual maximum daytime temperature (TXx) warming trends were evident. Estimation of the impact of irrigation and CA on the spatial average of the warming trends indicated that irrigation and CA have a pulse cooling effect on T2m and TXx, after which the warming trends increase at a greater rate than the control simulations. This differed at the local (subgrid) scale under irrigation where surface temperature cooling and the dampening of warming trends were both evident. As the local surface warming trends, in contrast to regional trends, do not account for atmospheric (water vapour) feedbacks, their dampening confirms the importance of atmospheric feedbacks (water vapour forcing) in explaining the enhanced regional trends. At the land surface, the positive radiative forcing signal arising from enhanced atmospheric water vapour is too weak to offset the local cooling from the irrigation-induced increase in the evaporative fraction. Our results underline that agricultural management has complex and non-negligible impacts on the local climate and highlight the need to evaluate the representation of land management in global climate models using climate models of higher resolution.

Mesoscale models are a class of atmospheric numerical model designed to simulate atmospheric phenomena with horizontal scales of about 2–200 km, although they are also applied to microscale phenomena with horizontal scales of less than about 2 km. Mesoscale models are capable of simulating wildland fire impacts on atmospheric flows if combustion byproducts (e.g., heat, smoke) are properly represented in the model. One of the primary challenges encountered in applying a mesoscale model to studies of fire-perturbed flows is the representation of the fire sensible heat source in the model. Two primary methods have been implemented previously: turbulent sensible heat flux, either in the form of an exponentially-decaying vertical heat flux profile or surface heat flux; and soil temperature perturbation. In this study, the ARPS-CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy submodel, is utilized to simulate the turbulent atmosphere during a low-intensity operational prescribed fire in the New Jersey Pine Barrens. The study takes place in two phases: model assessment and model sensitivity. In the model assessment phase, analysis is limited to a single control simulation in which the fire sensible heat source is represented as an exponentially decaying vertical profile of turbulent sensible heat flux. In the model sensitivity phase, a series of simulations are conducted to explore the sensitivity of model–observation agreement to (i) the method used to represent the fire sensible heat source in the model and (ii) parameters controlling the magnitude and vertical distribution of the sensible heat source. In both phases, momentum and scalar fields are compared between the model simulations and data obtained from six flux towers located within and adjacent to the burn unit. The multi-dimensional model assessment confirms that the model reproduces the background and fire-perturbed atmosphere as depicted by the tower observations, although the model underestimates the turbulent kinetic energy at the top of the canopy at several towers. The model sensitivity tests reveal that the best agreement with observations occurs when the fire sensible heat source is represented as a turbulent sensible heat flux profile, with surface heat flux magnitude corresponding to the peak 1 min mean observed heat flux averaged across the flux towers, and an e-folding extinction depth corresponding to the average canopy height in the burn unit. The study findings provide useful guidance for improving the representation of the sensible heat released from low-intensity prescribed fires in mesoscale models.

Methane emission fluxes from many facility-scale sources may be poorly quantified, potentially leading to uncertainties in the global methane budget. Accurate atmospheric measurement-based flux quantification is urgently required to address this. This paper describes the first test (using unbiased sampling) of a near-field Gaussian plume inversion (NGI) technique, suitable for facility-scale flux quantification, using a controlled release of methane gas. Two unmanned-aerial-vehicle (UAV) platforms were used to perform 22 flight surveys downwind of a point-source methane gas release from a regulated cylinder with a flowmeter. One UAV was tethered to an instrument on the ground, while the other UAV carried an on-board prototype instrument (both of which used the same near-infrared laser technology). Both instruments were calibrated using certified standards to account for variability in the instrumental gain factor, assuming fixed temperature and pressure. Furthermore, a water vapour correction factor, specifically calculated for the instrument, was applied and is described here in detail. We also provide guidance on potential systematic uncertainties associated with temperature and pressure, which may require further characterisation for improved measurement accuracy. The NGI technique was then used to derive emission fluxes for each UAV flight survey. We found good agreement of most NGI fluxes with the known controlled emission flux, within uncertainty, verifying the flux quantification methodology. The lower and upper NGI flux uncertainty bounds were, on average, 17 %±10(1σ) % and 227 %±98(1σ) % of the controlled emission flux, respectively. This range of conservative uncertainty bounds incorporate factors including the variability in the position of the time-invariant plume and potential for under-sampling. While these average uncertainties are large compared to methods such as tracer dispersion, we suggest that UAV sampling can be highly complementary to a toolkit of flux quantification approaches and may be a valuable alternative in situations where site access for tracer release is problematic. We see tracer release combined with UAV sampling as an effective approach in future flux quantification studies. Successful flux quantification using the UAV sampling methodology described here demonstrates its future utility in identifying and quantifying emissions from methane sources such as oil and gas extraction infrastructure facilities, livestock agriculture, and landfill sites, where site access may be difficult.

We present a new modelling approach for assessing atmospheric emissions from a city, using an aircraft measurement sampling strategy similar to that employed by previous mass balance studies. Unlike conventional mass balance methods, our approach does not assume that city-scale emissions are confined to a well-defined urban area and that peri-urban emissions are negligible. We apply our new approach to a case study conducted in March 2016, investigating CO, CH4 and CO2 emissions from a region focussed around Greater London using aircraft sampling of the downwind plume. For each species, we simulate the flux per unit area that would be observed at the aircraft sampling locations based on emissions from the UK national inventory, transported using a Lagrangian dispersion model. To reconcile this simulation with the measured flux per unit area, assuming the transport model is not biased, we require that inventory values of CO, CH4 and CO2 are scaled by 1.03, 0.71 and 1.61, respectively. However, our result for CO2 should not be considered a direct comparison with the inventory which only includes anthropogenic fluxes. For comparison, we also calculate fluxes using a conventional mass balance approach and compare these to the emissions inventory aggregated over the Greater London area. Using this method we derive much higher inventory scale factors for all three gases, as a direct consequence of the failure to account for emissions outside the Greater London boundary. That substantially different conclusions are drawn using the conventional mass balance method demonstrates the danger of using this technique for cities whose emissions cannot be separated from significant surrounding sources.

Abstract Secondary ice production (SIP) commonly occurs in coastal Antarctic stratocumulus, affecting their ice number concentrations (Nice) and radiative properties. However, SIP is poorly understood and crudely parametrized in models. By evaluating how well SIP is captured in a cloud‐resolving model, with a high‐resolution nest within a parent domain, we test how an improved comparison with aircraft observations affects the modeled cloud radiative properties. Under the assumption that primary ice is suitably represented by the model, we must enhance SIP by up to an order of magnitude to simulate observed Nice. Over the nest, a surface warming trend accompanied the SIP increase; however, this trend was not captured by the parent domain over the same region. Our results suggest that the radiative properties of microphysical features resolved in high‐resolution nested domains may not be captured by coarser domains, with implications for large‐scale radiative balance studies over the Antarctic continent.

The method of regularized stokeslets is widely used in microscale biological fluid dynamics due to its ease of implementation, natural treatment of complex moving geometries, and removal of singular functions to integrate. The standard implementation of the method is subject to high computational cost due to the coupling of the linear system size to the numerical resolution required to resolve the rapidly varying regularized stokeslet kernel. Here, we show how Richardson extrapolation with coarse values of the regularization parameter is ideally suited to reduce the quadrature error, hence dramatically reducing the storage and solution costs without loss of accuracy. Numerical experiments on the resistance and mobility problems in Stokes flow support the analysis, confirming several orders of magnitude improvement in accuracy and/or efficiency.

Climate change is likely to alter both flowering phenology and water availability for plants. Either of these changes alone can affect pollinator visitation and plant reproductive success. The relative impacts of phenology and water, and whether they interact in their impacts on plant reproductive success remain, however, largely unexplored. We manipulated flowering phenology and soil moisture in a factorial experiment with the subalpine perennial Mertensia ciliata (Boraginaceae). We examined responses of floral traits, floral abundance, pollinator visitation, and composition of visits by bumblebees vs. other pollinators. To determine the net effects on plant reproductive success, we also measured seed production and seed mass. Reduced water led to shorter, narrower flowers that produced less nectar. Late flowering plants produced fewer and shorter flowers. Both flowering phenology and water availability influenced pollination and reproductive success. Differences in flowering phenology had greater effects on pollinator visitation than did changes in water availability, but the reverse was true for seed production and mass, which were enhanced by greater water availability. The probability of receiving a flower visit declined over the season, coinciding with a decline in floral abundance in the arrays. Among plants receiving visits, both the visitation rate and percent of non-bumblebee visitors declined after the first week and remained low until the final week. We detected interactions of phenology and water on pollinator visitor composition, in which plants subject to drought were the only group to experience a late-season resurgence in visits by solitary bees and flies. Despite that interaction, net reproductive success measured as seed production responded additively to the two manipulations of water and phenology. Commonly observed declines in flower size and reward due to drought or shifts in phenology may not necessarily result in reduced plant reproductive success, which in M. ciliata responded more directly to water availability. The results highlight the need to go beyond studying single responses to climate changes, such as either phenology of a single species or how it experiences an abiotic factor, in order to understand how climate change may affect plant reproductive success.

Floral color plays a key role as visual signaling and is therefore of great importance in shaping plant-pollinator interactions. Iris (Iridaceae), a genus comprising over 300 species and named after the Greek goddess of the colorful rainbow, is famous for its dazzling palette of flower colors and patterns, which vary considerably both within and among species. Despite the large variation of flower color in Iris, little is known about the phylogenetic and ecological contexts of floral color. Here, we seek to resolve the evolution of flower color in the genus Iris in a macroevolutionary framework. We used a phylogenetic analysis to reconstruct the ancestral state of flower color and other pollination-related traits (e.g., the presence of nectar and mating system), and also tracked the evolution of color variation. We further explored weather floral trait transitions are better explained by environmental or pollinator-mediated selection. Our study revealed that the most recent common ancestor likely had monomorphic, purple flowers, with a crest and a spot on the fall. The flowers were likely insect-pollinated, nectar-rewarding, and self-compatible. The diversity of floral traits we see in modern irises, likely represents a trade-off between conflicting selection pressures. Whether shifts in these flower traits result from abiotic or biotic selective agents or are maintained by neutral processes without any selection remains an open question. Our analysis serves as a starting point for future work exploring the genetic and physiological mechanisms controlling flower coloration in the most color-diverse genus Iris.

A key challenge for numerical weather prediction models is representing boundary layer clouds in cold air outbreaks (CAOs). One important aspect is the evolution of microphysical properties as stratocumulus transitions to open cellular convection. Abel et al. (2017) have shown, for the first time from in situ field observations, that the break-up in CAOs over the eastern Atlantic may be controlled by the development of precipitation in the cloud system while the boundary layer becomes decoupled. This paper describes that case and examines in situ measurements from three more CAOs. Flights were conducted using the UK Facility for Airborne Atmospheric Measurements (FAAM) British Aerospace-146 (BAe-146) aircraft in the North Atlantic region around the UK, making detailed microphysical measurements in the stratiform boundary layer. As the cloudy boundary layer evolves prior to break-up, increasing liquid water paths (LWPs) and drop sizes and the formation of liquid precipitation are observed. Small numbers of ice particles, typically a few per litre, are also observed. Eventually LWPs reduce significantly due to loss of water from the stratocumulus cloud (SC) layer. In three of the cases, aerosols are removed from the boundary layer across the transition. This process appears to be similar to those observed in warm clouds and pockets of open cells (POCs) in the subtropics. After break-up, deeper convective clouds form with bases warm enough for secondary ice production (SIP), leading to rapid glaciation. It is concluded that the precipitation is strongly associated with the break-up, with both weakening of the capping inversion and boundary layer decoupling also observed.

Primary biological aerosol including bacteria, fungal spores and pollen have important implications for public health and the environment. Such particles may have different concentrations of chemical fluorophores and will respond differently in the presence of ultraviolet light, potentially allowing for different types of biological aerosol to be discriminated. Development of ultraviolet light induced fluorescence (UV-LIF) instruments such as the Wideband Integrated Bioaerosol Sensor (WIBS) has allowed for size, morphology and fluorescence measurements to be collected in real-time. However, it is unclear without studying instrument responses in the laboratory, the extent to which different types of particles can be discriminated. Collection of laboratory data is vital to validate any approach used to analyse data and ensure that the data available is utilized as effectively as possible.In this paper a variety of methodologies are tested on a range of particles collected in the laboratory. Hierarchical agglomerative clustering (HAC) has been previously applied to UV-LIF data in a number of studies and is tested alongside other algorithms that could be used to solve the classification problem: Density Based Spectral Clustering and Noise (DBSCAN), k-means and gradient boosting.Whilst HAC was able to effectively discriminate between reference narrow-size distribution PSL particles, yielding a classification error of only 1.8 %, similar results were not obtained when testing on laboratory generated aerosol where the classification error was found to be between 11.5 % and 24.2 %. Furthermore, there is a large uncertainty in this approach in terms of the data preparation and the cluster index used, and we were unable to attain consistent results across the different sets of laboratory generated aerosol tested.The lowest classification errors were obtained using gradient boosting, where the misclassification rate was between 4.38 % and 5.42 %. The largest contribution to the error, in the case of the higher misclassification rate, was the pollen samples where 28.5 % of the samples were incorrectly classified as fungal spores. The technique was robust to changes in data preparation provided a fluorescent threshold was applied to the data.In the event that laboratory training data are unavailable, DBSCAN was found to be a potential alternative to HAC. In the case of one of the data sets where 22.9 % of the data were left unclassified we were able to produce three distinct clusters obtaining a classification error of only 1.42 % on the classified data. These results could not be replicated for the other data set where 26.8 % of the data were not classified and a classification error of 13.8 % was obtained. This method, like HAC, also appeared to be heavily dependent on data preparation, requiring a different selection of parameters depending on the preparation used. Further analysis will also be required to confirm our selection of the parameters when using this method on ambient data.There is a clear need for the collection of additional laboratory generated aerosol to improve interpretation of current databases and to aid in the analysis of data collected from an ambient environment. New instruments with a greater resolution are likely to improve on current discrimination between pollen, bacteria and fungal spores and even between different species, however the need for extensive laboratory data sets will grow as a result.

We describe the motivation, design, and execution of the Greenhouse gAs Uk and Global Emissions (GAUGE) project. The overarching scientific objective of GAUGE was to use atmospheric data to estimate the magnitude, distribution, and uncertainty of the UK greenhouse gas (GHG, defined here as CO2, CH4, and N2O) budget, 2013–2015. To address this objective, we established a multi-year and interlinked measurement and data analysis programme, building on an established tall-tower GHG measurement network. The calibrated measurement network comprises ground-based, airborne, ship-borne, balloon-borne, and space-borne GHG sensors. Our choice of measurement technologies and measurement locations reflects the heterogeneity of UK GHG sources, which range from small point sources such as landfills to large, diffuse sources such as agriculture. Atmospheric mole fraction data collected at the tall towers and on the ships provide information on sub-continental fluxes, representing the backbone to the GAUGE network. Additional spatial and temporal details of GHG fluxes over East Anglia were inferred from data collected by a regional network. Data collected during aircraft flights were used to study the transport of GHGs on local and regional scales. We purposely integrated new sensor and platform technologies into the GAUGE network, allowing us to lay the foundations of a strengthened UK capability to verify national GHG emissions beyond the project lifetime. For example, current satellites provide sparse and seasonally uneven sampling over the UK mainly because of its geographical size and cloud cover. This situation will improve with new and future satellite instruments, e.g. measurements of CH4 from the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P. We use global, nested, and regional atmospheric transport models and inverse methods to infer geographically resolved CO2 and CH4 fluxes. This multi-model approach allows us to study model spread in a posteriori flux estimates. These models are used to determine the relative importance of different measurements to infer the UK GHG budget. Attributing observed GHG variations to specific sources is a major challenge. Within a UK-wide spatial context we used two approaches: (1) Δ14CO2 and other relevant isotopologues (e.g. δ13CCH4) from collected air samples to quantify the contribution from fossil fuel combustion and other sources, and (2) geographical separation of individual sources, e.g. agriculture, using a high-density measurement network. Neither of these represents a definitive approach, but they will provide invaluable information about GHG source attribution when they are adopted as part of a more comprehensive, long-term national GHG measurement programme. We also conducted a number of case studies, including an instrumented landfill experiment that provided a test bed for new technologies and flux estimation methods. We anticipate that results from the GAUGE project will help inform other countries on how to use atmospheric data to quantify their nationally determined contributions to the Paris Agreement.

We demonstrate, for the first time, continuous real-time observations of airborne bio-fluorescent aerosols recorded at the British Antarctic Survey's Halley VI Research Station, located on the Brunt Ice Shelf close to the Weddell Sea coast (lat 75°34′59′′ S, long 26°10′0′′ W) during Antarctic summer, 2015. As part of the NERC MAC (Microphysics of Antarctic Clouds) aircraft aerosol cloud interaction project, observations with a real-time ultraviolet-light-induced fluorescence (UV-LIF) spectrometer were conducted to quantify airborne biological containing particle concentrations along with dust particles as a function of wind speed and direction over a 3-week period. Significant, intermittent enhancements of both non- and bio-fluorescent particles were observed to varying degrees in very specific wind directions and during strong wind events. Analysis of the particle UV-induced emission spectra, particle sizes and shapes recorded during these events suggest the majority of particles were likely a subset of dust with weak fluorescence emission responses. A minor fraction, however, were likely primary biological particles that were very strongly fluorescent, with a subset identified as likely being pollen based on comparison with laboratory data obtained using the same instrument. A strong correlation of bio-fluorescent particles with wind speed was observed in some, but not all, periods. Interestingly, the fraction of fluorescent particles to total particle concentration also increased significantly with wind speed during these events. The enhancement in concentrations of these particles could be interpreted as due to resuspension from the local ice surface but more likely due to emissions from distal sources within Antarctica as well as intercontinental transport. Likely distal sources identified by back trajectory analyses and dispersion modelling were the coastal ice margin zones in Halley Bay consisting of bird colonies with likely associated high bacterial activity together with contributions from exposed ice margin bacterial colonies but also long-range transport from the southern coasts of Argentina and Chile. Dispersion modelling also demonstrated emissions from shipping lanes, and therefore marine anthropogenic sources cannot be ruled out. Average total concentrations of total fluorescent aerosols were found to be 1.9 ± 2.6 L−1 over a 3-week period crossing over from November into December, but peak concentrations during intermittent enhancement events could be up to several tens per litre. While this short pilot study is not intended to be generally representative of Antarctic aerosol, it demonstrates the usefulness of the UV-LIF measurement technique for quantification of airborne bioaerosol concentrations and to understand their dispersion. The potential importance for microbial colonisation of Antarctica is highlighted.

The degree of glaciation of mixed-phase clouds constitutes one of the largest uncertainties in climate prediction. In order to better understand cloud glaciation, cloud spectrometer observations are presented in this paper, which were made in the mixed-phase temperature regime between 0 and −38 °C (273 to 235 K), where cloud particles can either be frozen or liquid. The extensive data set covers four airborne field campaigns providing a total of 139 000 1 Hz data points (38.6 h within clouds) over Arctic, midlatitude and tropical regions. We develop algorithms, combining the information on number concentration, size and asphericity of the observed cloud particles to classify four cloud types: liquid clouds, clouds in which liquid droplets and ice crystals coexist, fully glaciated clouds after the Wegener–Bergeron–Findeisen process and clouds where secondary ice formation occurred. We quantify the occurrence of these cloud groups depending on the geographical region and temperature and find that liquid clouds dominate our measurements during the Arctic spring, while clouds dominated by the Wegener–Bergeron–Findeisen process are most common in midlatitude spring. The coexistence of liquid water and ice crystals is found over the whole mixed-phase temperature range in tropical convective towers in the dry season. Secondary ice is found at midlatitudes at −5 to −10 °C (268 to 263 K) and at higher altitudes, i.e. lower temperatures in the tropics. The distribution of the cloud types with decreasing temperature is shown to be consistent with the theory of evolution of mixed-phase clouds. With this study, we aim to contribute to a large statistical database on cloud types in the mixed-phase temperature regime.

Characterisation of bioaerosols has important implications within environment and public health sectors. Recent developments in ultraviolet light-induced fluorescence (UV-LIF) detectors such as the Wideband Integrated Bioaerosol Spectrometer (WIBS) and the newly introduced Multiparameter Bioaerosol Spectrometer (MBS) have allowed for the real-time collection of fluorescence, size and morphology measurements for the purpose of discriminating between bacteria, fungal spores and pollen.This new generation of instruments has enabled ever larger data sets to be compiled with the aim of studying more complex environments. In real world data sets, particularly those from an urban environment, the population may be dominated by non-biological fluorescent interferents, bringing into question the accuracy of measurements of quantities such as concentrations. It is therefore imperative that we validate the performance of different algorithms which can be used for the task of classification.For unsupervised learning we tested hierarchical agglomerative clustering with various different linkages. For supervised learning, 11 methods were tested, including decision trees, ensemble methods (random forests, gradient boosting and AdaBoost), two implementations for support vector machines (libsvm and liblinear) and Gaussian methods (Gaussian naïve Bayesian, quadratic and linear discriminant analysis, the k-nearest neighbours algorithm and artificial neural networks).The methods were applied to two different data sets produced using the new MBS, which provides multichannel UV-LIF fluorescence signatures for single airborne biological particles. The first data set contained mixed PSLs and the second contained a variety of laboratory-generated aerosol.Clustering in general performs slightly worse than the supervised learning methods, correctly classifying, at best, only 67. 6 and 91. 1 % for the two data sets respectively. For supervised learning the gradient boosting algorithm was found to be the most effective, on average correctly classifying 82. 8 and 98. 27 % of the testing data, respectively, across the two data sets.A possible alternative to gradient boosting is neural networks. We do however note that this method requires much more user input than the other methods, and we suggest that further research should be conducted using this method, especially using parallelised hardware such as the GPU, which would allow for larger networks to be trained, which could possibly yield better results.We also saw that some methods, such as clustering, failed to utilise the additional shape information provided by the instrument, whilst for others, such as the decision trees, ensemble methods and neural networks, improved performance could be attained with the inclusion of such information.

In situ airborne observations of cloud microphysics, aerosol properties, and thermodynamic structure over the transition from sea ice to ocean are presented from the Aerosol-Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) campaign. A case study from 23 March 2013 provides a unique view of the cloud microphysical changes over this transition under cold-air outbreak conditions. Cloud base lifted and cloud depth increased over the transition from sea ice to ocean. Mean droplet number concentrations, Ndrop, also increased from 110 ± 36 cm−3 over the sea ice to 145 ± 54 cm−3 over the marginal ice zone (MIZ). Downstream over the ocean, Ndrop decreased to 63 ± 30 cm−3. This reduction was attributed to enhanced collision-coalescence of droplets within the deep ocean cloud layer. The liquid water content increased almost four fold over the transition and this, in conjunction with the deeper cloud layer, allowed rimed snowflakes to develop and precipitate out of cloud base downstream over the ocean. The ice properties of the cloud remained approximately constant over the transition. Observed ice crystal number concentrations averaged approximately 0.5–1.5 L−1, suggesting only primary ice nucleation was active; however, there was evidence of crystal fragmentation at cloud base over the ocean. Little variation in aerosol particle number concentrations was observed between the different surface conditions; however, some variability with altitude was observed, with notably greater concentrations measured at higher altitudes ( > 800 m) over the sea ice. Near-surface boundary layer temperatures increased by 13 °C from sea ice to ocean, with corresponding increases in surface heat fluxes and turbulent kinetic energy. These significant thermodynamic changes were concluded to be the primary driver of the microphysical evolution of the cloud. This study represents the first investigation, using in situ airborne observations, of cloud microphysical changes with changing sea ice cover and addresses the question of how the microphysics of Arctic stratiform clouds may change as the region warms and sea ice extent reduces.

Heavy rainfall from convective clouds can lead to devastating flash flooding, and observations of aerosols and clouds are required to improve cloud parameterisations used in precipitation forecasts. We present measurements of boundary layer aerosol concentration, size, and composition from a series of research flights performed over the southwest peninsula of the UK during the COnvective Precipitation Experiment (COPE) of summer 2013. We place emphasis on periods of southwesterly winds, which locally are most conducive to convective cloud formation, when marine air from the Atlantic reached the peninsula. Accumulation-mode aerosol mass loadings were typically 2–3 µg m−3 (corrected to standard cubic metres at 1013.25 hPa and 273.15 K), the majority of which was sulfuric acid over the sea, or ammonium sulfate inland, as terrestrial ammonia sources neutralised the aerosol. The cloud condensation nuclei (CCN) concentrations in these conditions were ∼ 150–280 cm−3 at 0.1 % and 400–500 cm−3 at 0.9 % supersaturation (SST), which are in good agreement with previous Atlantic measurements, and the cloud drop concentrations at cloud base ranged from 100 to 500 cm−3. The concentration of CCN at 0.1 % SST was well correlated with non-sea-salt sulfate, meaning marine sulfate formation was likely the main source of CCN. Marine organic aerosol (OA) had a similar mass spectrum to previous measurements of sea spray OA and was poorly correlated with CCN. In one case study that was significantly different to the rest, polluted anthropogenic emissions from the southern and central UK advected to the peninsula, with significant enhancements of OA, ammonium nitrate and sulfate, and black carbon. The CCN concentrations here were around 6 times higher than in the clean cases, and the cloud drop number concentrations were 3–4 times higher. Sources of ice-nucleating particles (INPs) were assessed by comparing different parameterisations used to predict INP concentrations, using measured aerosol concentrations as input. The parameterisations based on total aerosol produced INP concentrations that agreed within an order of magnitude with measured first ice concentrations at cloud temperatures as low as −12 °C. Composition-specific parameterisations for mineral dust, fluorescent particles, and sea spray OA were 3–4 orders of magnitude lower than the measured first ice concentrations, meaning a source of INPs was present that was not characterised by our measurements and/or one or more of the composition-specific parameterisations greatly underestimated INPs in this environment.

The Amazon basin is a vast continental area in which atmospheric composition is relatively unaffected by anthropogenic aerosol particles. Understanding the properties of the natural biogenic aerosol particles over the Amazon rainforest is key to understanding their influence on regional and global climate. While there have been a number of studies during the wet season, and of biomass burning particles in the dry season, there has been relatively little work on the transition period – the start of the dry season in the absence of biomass burning. As part of the Brazil–UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) project, aerosol measurements, focussing on unpolluted biogenic air masses, were conducted at a remote rainforest site in the central Amazon during the transition from wet to dry season in July 2013. This period marks the start of the dry season but before significant biomass burning occurs in the region. Median particle number concentrations were 266 cm−3, with size distributions dominated by an accumulation mode of 130–150 nm. During periods of low particle counts, a smaller Aitken mode could also be seen around 80 nm. While the concentrations were similar in magnitude to those seen during the wet season, the size distributions suggest an enhancement in the accumulation mode compared to the wet season, but not yet to the extent seen later in the dry season, when significant biomass burning takes place. Submicron nonrefractory aerosol composition, as measured by an aerosol chemical speciation monitor (ACSM), was dominated by organic material (around 81 %). Aerosol hygroscopicity was probed using measurements from a hygroscopicity tandem differential mobility analyser (HTDMA), and a quasi-monodisperse cloud condensation nuclei counter (CCNc). The hygroscopicity parameter, κ, was found to be low, ranging from 0.12 for Aitken-mode particles to 0.18 for accumulation-mode particles. This was consistent with previous studies in the region, but lower than similar measurements conducted in Borneo, where κ ranged 0.17–0.37. A wide issue bioaerosol sensor (WIBS-3M) was deployed at ground level to probe the coarse mode, detecting primary biological aerosol by fluorescence (fluorescent biological aerosol particles, or FBAPs). The mean FBAP number concentration was 400 ± 242 L−1; however, this ranged from around 200 L−1 during the day to as much as 1200 L−1 at night. FBAPs dominated the coarse-mode particles, comprising between 55 and 75 % of particles during the day to more than 90 % at night. Non-FBAPs did not show a strong diurnal pattern. Comparison with previous FBAP measurements above canopy at the same location suggests there is a strong vertical gradient in FBAP concentrations through the canopy. Cluster analysis of the data suggests that FBAPs were dominated (around 70 %) by fungal spores. Further, long-term measurements will be required in order to fully examine the seasonal variability and distribution of primary biological aerosol particles through the canopy. This is the first time that such a suite of measurements has been deployed at this site to investigate the chemical composition and properties of the biogenic contributions to Amazonian aerosol during the transition period from the wet to the dry season, and thus provides a unique comparison to the aerosol properties observed during the wet season in previous similar campaigns. This was also the first deployment of a WIBS in the Amazon rainforest to study coarse-mode particles, particularly primary biological aerosol particles, which are likely to play an important role as ice nuclei in the region.

There are strong indications that particles containing secondary organic aerosol (SOA) exhibit amorphous solid or semi-solid phase states in the atmosphere. This may facilitate heterogeneous ice nucleation and thus influence cloud properties. However, experimental ice nucleation studies of biogenic SOA are scarce. Here, we investigated the ice nucleation ability of viscous SOA particles. The SOA particles were produced from the ozone initiated oxidation of α-pinene in an aerosol chamber at temperatures in the range from −38 to −10 °C at 5–15 % relative humidity with respect to water to ensure their formation in a highly viscous phase state, i.e. semi-solid or glassy. The ice nucleation ability of SOA particles with different sizes was investigated with a new continuous flow diffusion chamber. For the first time, we observed heterogeneous ice nucleation of viscous α-pinene SOA for ice saturation ratios between 1.3 and 1.4 significantly below the homogeneous freezing limit. The maximum frozen fractions found at temperatures between −39.0 and −37.2 °C ranged from 6 to 20 % and did not depend on the particle surface area. Global modelling of monoterpene SOA particles suggests that viscous biogenic SOA particles are indeed present in regions where cirrus cloud formation takes place. Hence, they could make up an important contribution to the global ice nucleating particle budget.

This paper assesses the reasons for high ice number concentrations observed in orographic clouds by comparing in situ measurements from the Ice NUcleation Process Investigation And Quantification field campaign (INUPIAQ) at Jungfraujoch, Switzerland (3570 m a.s.l.) with the Weather Research and Forecasting model (WRF) simulations over real terrain surrounding Jungfraujoch. During the 2014 winter field campaign, between 20 January and 28 February, the model simulations regularly underpredicted the observed ice number concentration by 103 L−1. Previous literature has proposed several processes for the high ice number concentrations in orographic clouds, including an increased ice nucleating particle (INP) concentration, secondary ice multiplication and the advection of surface ice crystals into orographic clouds. We find that increasing INP concentrations in the model prevents the simulation of the mixed-phase clouds that were witnessed during the INUPIAQ campaign at Jungfraujoch. Additionally, the inclusion of secondary ice production upwind of Jungfraujoch into the WRF simulations cannot consistently produce enough ice splinters to match the observed concentrations. A flux of surface hoar crystals was included in the WRF model, which simulated ice concentrations comparable to the measured ice number concentrations, without depleting the liquid water content (LWC) simulated in the model. Our simulations therefore suggest that high ice concentrations observed in mixed-phase clouds at Jungfraujoch are caused by a flux of surface hoar crystals into the orographic clouds.

Dissolved organic nitrogen (DON) contributes significantly to the overall nitrogen budget, but is not routinely measured in precipitation or stream water. In order to investigate the contribution of DON to the deposition and export of N, precipitation, stream and soil water samples were collected from an ombrotrophic peatland and analysed for DON over a 2-year period. In wet-only deposition DON contributed up to 10 % of the total dissolved nitrogen (TDN) and was the most dominant fraction in soil water (99 %) and stream water (75 %). NH4+ was the most dominate form of N in precipitation, with NO3− contributing the least to precipitation, soil water and stream water. Precipitation and stream DON were qualitatively analysed by a two-dimensional gas chromatograph coupled to a nitrogen chemiluminescence detector (GC × GC-NCD) after trapping onto C18 solid phase extraction (SPE) cartridges. Ten unique compounds were detected and five identified as pyrrole, benzonitrile, dodecylamine, N-nitrosodipropylamine and decylamine. Five compounds were present in both precipitation and stream samples: pyrrole, benzonitrile and three unidentified compounds. The SPE-extraction efficiency for DON was very low (11 %), but with improvements DON speciation could become a valuable tool to provide information on its sources and pathways and inform chemical transport models.

Single-particle compositional analysis of filter samples collected on board the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft is presented for six flights during the springtime Aerosol–Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign (March–April 2013). Scanning electron microscopy was utilised to derive size-segregated particle compositions and size distributions, and these were compared to corresponding data from wing-mounted optical particle counters. Reasonable agreement between the calculated number size distributions was found. Significant variability in composition was observed, with differing external and internal mixing identified, between air mass trajectory cases based on HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) analyses. Dominant particle classes were silicate-based dusts and sea salts, with particles notably rich in K and Ca detected in one case. Source regions varied from the Arctic Ocean and Greenland through to northern Russia and the European continent. Good agreement between the back trajectories was mirrored by comparable compositional trends between samples. Silicate dusts were identified in all cases, and the elemental composition of the dust was consistent for all samples except one. It is hypothesised that long-range, high-altitude transport was primarily responsible for this dust, with likely sources including the Asian arid regions.

Cloud microphysical processes involving the ice phase in tropospheric clouds are among the major uncertainties in cloud formation, weather, and general circulation models. The detection of aerosol particles, liquid droplets, and ice crystals, especially in the small cloud particle-size range below 50 μm, remains challenging in mixed phase, often unstable environments. The Cloud Aerosol Spectrometer with Polarization (CASPOL) is an airborne instrument that has the ability to detect such small cloud particles and measure the variability in polarization state of their backscattered light. Here we operate the versatile Cosmics Leaving OUtdoor Droplets (CLOUD) chamber facility at the European Organization for Nuclear Research (CERN) to produce controlled mixed phase and other clouds by adiabatic expansions in an ultraclean environment, and use the CASPOL to discriminate between different aerosols, water, and ice particles. In this paper, optical property measurements of mixed-phase clouds and viscous secondary organic aerosol (SOA) are presented. We report observations of significant liquid–viscous SOA particle polarization transitions under dry conditions using CASPOL. Cluster analysis techniques were subsequently used to classify different types of particles according to their polarization ratios during phase transition. A classification map is presented for water droplets, organic aerosol (e.g., SOA and oxalic acid), crystalline substances such as ammonium sulfate, and volcanic ash. Finally, we discuss the benefits and limitations of this classification approach for atmospherically relevant concentrations and mixtures with respect to the CLOUD 8–9 campaigns and its potential contribution to tropical troposphere layer analysis.

The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and −10 °C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion – pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and −10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, super-cooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 °C is correct.

The fluorescent nature of aerosol at a high-altitude Alpine site was studied using a wide-band integrated bioaerosol (WIBS-4) single particle multi-channel ultraviolet – light-induced fluorescence (UV-LIF) spectrometer. This was supported by comprehensive cloud microphysics and meteorological measurements with the aims of cataloguing concentrations of bio-fluorescent aerosols at this high-altitude site and also investigating possible influences of UV–fluorescent particle types on cloud–aerosol processes. Analysis of background free tropospheric air masses, using a total aerosol inlet, showed there to be a minor increase in the fluorescent aerosol fraction during in-cloud cases compared to out-of-cloud cases. The size dependence of the fluorescent aerosol fraction showed the larger aerosol to be more likely to be fluorescent with 80 % of 10 μm particles being fluorescent. Whilst the fluorescent particles were in the minority (NFl∕NAll = 0.27 ± 0.19), a new hierarchical agglomerative cluster analysis approach, Crawford et al. (2015) revealed the majority of the fluorescent aerosols were likely to be representative of fluorescent mineral dust. A minor episodic contribution from a cluster likely to be representative of primary biological aerosol particles (PBAP) was also observed with a wintertime baseline concentration of 0.1 ± 0.4 L−1. Given the low concentration of this cluster and the typically low ice-active fraction of studied PBAP (e.g. pseudomonas syringae), we suggest that the contribution to the observed ice crystal concentration at this location is not significant during the wintertime.

We present microphysical observations of cumulus clouds measured over the southwest peninsula of the UK during the COnvective Precipitation Experiment (COPE) in August 2013, which are framed into a wider context using ground-based and airborne radar measurements. Two lines of cumulus clouds formed in the early afternoon along convergence lines aligned with the peninsula. The lines became longer and broader during the afternoon due to new cell formation and stratiform regions forming downwind of the convective cells. Ice concentrations up to 350 L−1, well in excess of the expected ice nuclei (IN) concentrations, were measured in the mature stratiform regions, suggesting that secondary ice production was active. Detailed sampling focused on an isolated liquid cloud that glaciated as it matured to merge with a band of cloud downwind. In the initial cell, drizzle concentrations increased from ∼ 0.5 to ∼ 20 L−1 in around 20 min. Ice concentrations developed up to a few per litre, which is around the level expected of primary IN. The ice images were most consistent with freezing drizzle, rather than smaller cloud drops or interstitial IN forming the first ice. As new cells emerged in and around the cloud, ice concentrations up to 2 orders of magnitude higher than the predicted IN concentrations developed, and the cloud glaciated over a period of 12–15 min. Almost all of the first ice particles to be observed were frozen drops, while vapour-grown ice crystals were dominant in the latter stages. Our observations are consistent with the production of large numbers of small secondary ice crystals/fragments, by a mechanism such as Hallett–Mossop or droplets shattering upon freezing. Some of the small ice froze drizzle drops on contact, while others grew more slowly by vapour deposition. Graupel and columns were seen in cloud penetrations up to the −12 °C level, though many ice particles were mixed habit due to riming and growth by vapour deposition at multiple temperatures. Our observations demonstrate that the freezing of drizzle/raindrops is an important process that dominates the formation of large ice in the intermediate stages of cloud development. As these frozen drops were the first precipitation observed, interactions between the warm-rain and secondary ice production processes appear to be key to determining the timing and location of precipitation.

Spectroscopic measurements of atmospheric N2O and CH4 mole fractions were made on board the FAAM (Facility for Airborne Atmospheric Measurements) large atmospheric research aircraft. We present details of the mid-infrared quantum cascade laser absorption spectrometer (QCLAS, Aerodyne Research Inc., USA) employed, including its configuration for airborne sampling, and evaluate its performance over 17 flights conducted during summer 2014. Two different methods of correcting for the influence of water vapour on the spectroscopic retrievals are compared and evaluated. A new in-flight calibration procedure to account for the observed sensitivity of the instrument to ambient pressure changes is described, and its impact on instrument performance is assessed. Test flight data linking this sensitivity to changes in cabin pressure are presented. Total 1σ uncertainties of 2.47 ppb for CH4 and 0.54 ppb for N2O are derived. We report a mean difference in 1 Hz CH4 mole fraction of 2.05 ppb (1σ = 5.85 ppb) between in-flight measurements made using the QCLAS and simultaneous measurements using a previously characterised Fast Greenhouse Gas Analyser (FGGA, Los Gatos Research, USA). Finally, a potential case study for the estimation of a regional N2O flux using a mass balance technique is identified, and the method for calculating such an estimate is outlined.

In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio–hydro–atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen–Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misattribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed, yielding an explicit cluster attribution for each particle and improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

During the winter of 2013 and 2014 measurements of cloud microphysical properties over a 5-week period at the high-alpine site Jungfraujoch, Switzerland, were carried out as part of the Cloud Aerosol Characterisation Experiments (CLACE) and the Ice Nucleation Process Investigation and Quantification project (INUPIAQ). Measurements of aerosol properties at a second, lower site, Schilthorn, Switzerland, were used as input for a primary ice nucleation scheme to predict ice nuclei concentrations at Jungfraujoch. Frequent, rapid transitions in the ice and liquid properties of the clouds at Jungfraujoch were identified that led to large fluctuations in ice mass fractions over temporal scales of seconds to hours. During the measurement period we observed high concentrations of ice particles that exceeded 1000 L−1 at temperatures around −15 °C, verified by multiple instruments. These concentrations could not be explained using the usual primary ice nucleation schemes, which predicted ice nucleus concentrations several orders of magnitude smaller than the peak ice crystal number concentrations. Secondary ice production through the Hallett–Mossop process as a possible explanation was ruled out, as the cloud was rarely within the active temperature range for this process. It is shown that other mechanisms of secondary ice particle production cannot explain the highest ice particle concentrations. We describe four possible mechanisms that could lead to high cloud ice concentrations generated from the snow-covered surfaces surrounding the measurement site. Of these we show that hoar frost crystals generated at the cloud enveloped snow surface could be the most important source of cloud ice concentrations. Blowing snow was also observed to make significant contributions at higher wind speeds when ice crystal concentrations were < 100 L−1.

Black carbon aerosol (BC) deposited to the Arctic sea ice or present in the free troposphere can significantly affect the Earth's radiation budget at high latitudes yet the BC burden in these regions and the regional source contributions are poorly constrained. Aircraft measurements of aerosol composition in the European Arctic were conducted during the Aerosol–Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) campaign in March 2013. Pollutant plumes were encountered throughout the lower to upper Arctic troposphere featuring enhancements in CO and aerosol mass loadings, which were chemically speciated into BC and non-refractory sulphate and organic matter. FLEXPART-WRF simulations have been performed to evaluate the likely contribution to the pollutants from regional ground sources. By combining up-to-date anthropogenic and open fire biomass burning (OBB) inventories, we have been able to compare the contributions made to the observed pollution layers from the sources of eastern/northern Asia (AS), Europe (EU) and North America (NA). Over 90 % of the contribution to the BC was shown to arise from non-OBB anthropogenic sources. AS sources were found to be the major contributor to the BC burden, increasing background BC loadings by a factor of 3–5 to 100.8 ± 48.4 ng sm−3 (in standard air m3 at 273.15 K and 1013.25 mbar) and 55.8 ± 22.4 ng sm−3 in the middle and upper troposphere respectively. AS plumes close to the tropopause (about 7.5–8 km) were also observed, with BC concentrations ranging from 55 to 73 ng sm−3, which will potentially have a significant radiative impact. EU sources influenced the middle troposphere with a BC mean concentration of 70.8 ± 39.1 ng sm−3 but made a minor contribution to the upper troposphere due to the relatively high latitude of the source region. The contribution of NA was shown to be much lower at all altitudes with BC mean concentration of 20 ng sm−3. The BC transported to the Arctic is mixed with a non-BC volume fraction representing between 90–95 % of the mass, and has a relatively uniform core size distribution with mass median diameter 190–210 nm and geometric standard deviation σg = 1.55–1.65 and this varied little across all source regions. It is estimated that 60–95 % of BC is scavenged between emission and receptor based on BC / ΔCO comparisons between source inventories and measurement. We show that during the springtime of 2013, the anthropogenic pollution particularly from sources in Asia, contributed significantly to BC across the European Arctic free troposphere. In contrast to previous studies, the contribution from open wildfires was minimal. Given that Asian pollution is likely to continue to rise over the coming years, it is likely that the radiative forcing in the Arctic will also continue to increase.

For the first time, the behaviour of non-refractory inorganic and organic submicron particulate through an entire annual cycle is investigated using measurements from an Aerodyne compact time-of-flight aerosol mass spectrometer (cToF-AMS) located at a UK urban background site in North Kensington, London. We show that secondary aerosols account for a significant fraction of the submicron aerosol burden and that high concentration events are governed by different factors depending on season. Furthermore, we demonstrate that on an annual basis there is no variability in the extent of secondary organic aerosol (SOA) oxidation, as defined by the oxygen content, irrespective of amount. This result is surprising given the changes in precursor emissions and contributions as well as photochemical activity throughout the year; however it may make the characterisation of SOA in urban environments more straightforward than previously supposed. Organic species, nitrate, sulphate, ammonium, and chloride were measured during 2012 with average concentrations (±1 standard deviation) of 4.32 (±4.42), 2.74 (±5.00), 1.39 (±1.34), 1.30 (±1.52), and 0.15 (±0.24) μg m−3, contributing 44, 28, 14, 13, and 2 % to the total non-refractory submicron mass (NR-PM1) respectively. Components of the organic aerosol fraction are determined using positive matrix factorisation (PMF), in which five factors are identified and attributed as hydrocarbon-like OA (HOA), cooking OA (COA), solid fuel OA (SFOA), type 1 oxygenated OA (OOA1), and type 2 oxygenated OA (OOA2). OOA1 and OOA2 represent more and less oxygenated OA with average concentrations of 1.27 (±1.49) and 0.14 (±0.29) μg m−3 respectively, where OOA1 dominates the SOA fraction (90%). Diurnal, monthly, and seasonal trends are observed in all organic and inorganic species due to meteorological conditions, specific nature of the aerosols, and availability of precursors. Regional and transboundary pollution as well as other individual pollution events influence London's total submicron aerosol burden. High concentrations of non-refractory submicron aerosols in London are governed by particulate emissions in winter, especially nitrate and SFOA, whereas SOA formation drives the high concentrations during the summer. The findings from this work could have significant implications for modelling of urban air pollution as well as for the effects of atmospheric aerosols on health and climate.

Measurements from four case studies in spring and summer-time Arctic stratocumulus clouds during the Aerosol-Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) campaign are presented. We compare microphysics observations between cases and with previous measurements made in the Arctic and Antarctic. During ACCACIA, stratocumulus clouds were observed to consist of liquid at cloud tops, often at distinct temperature inversions. The cloud top regions precipitated low concentrations of ice into the cloud below. During the spring cases median ice number concentrations (~ 0.5 L−1) were found to be lower by about a factor of 5 than observations from the summer campaign (~ 3 L−1). Cloud layers in the summer spanned a warmer temperature regime than in the spring and enhancement of ice concentrations in these cases was found to be due to secondary ice production through the Hallett–Mossop (H–M) process. Aerosol concentrations during spring ranged from ~ 300–400 cm−3 in one case to lower values of ~ 50–100 cm−3 in the other. The concentration of aerosol with sizes Dp > 0.5 μm was used in a primary ice nucleus (IN) prediction scheme (DeMott et al., 2010). Predicted IN values varied depending on aerosol measurement periods but were generally greater than maximum observed median values of ice crystal concentrations in the spring cases, and less than the observed ice concentrations in the summer due to the influence of secondary ice production. Comparison with recent cloud observations in the Antarctic summer (Grosvenor et al., 2012), reveals lower ice concentrations in Antarctic clouds in comparable seasons. An enhancement of ice crystal number concentrations (when compared with predicted IN numbers) was also found in Antarctic stratocumulus clouds spanning the H–M temperature zone; however, concentrations were about an order of magnitude lower than those observed in the Arctic summer cases but were similar to the peak values observed in the colder Arctic spring cases, where the H–M mechanism did not operate.

Solid fuel emissions, including those from biomass burning, are increasing in urban areas across the European Union due to rising energy costs and government incentives to use renewable energy sources for heating. In order to help protect human health as well as to improve air quality and pollution abatement strategies, the sources of combustion aerosols, their contributions, and the processes they undergo need to be better understood. A high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) was therefore deployed at an urban background site between January and February 2012 to investigate solid fuel organic aerosols (SFOA) in London. The variability of SFOA was examined and the factors governing the split between the two SFOA factors derived from Positive Matrix Factorisation (PMF) were assessed. The concentrations of both factors were found to increase during the night and during cold periods, consistent with domestic space heating activities. The split between the two factors is likely governed predominantly by differences in burn conditions where SFOA1 best represents more efficient burns and SFOA2 best represents less efficient burns. The differences in efficiency may be due to burner types or burn phase, for example. Different fuel types and levels of atmospheric processing also likely contribute to the two factors. As the mass spectral profile of SFOA is highly variable, the findings from this study may have implications for improving future source apportionment and factorisation analyses. During the winter, SFOA was found to contribute 38% to the total non-refractory submicron organic aerosol (OA) mass, with similar contributions from both SFOA factors (20% from SFOA1 and 18% from SFOA2). A similar contribution of SFOA was derived for the same period from a compact time-of-flight AMS (cToF-AMS), which measured for a full calendar year at the same site. The seasonality of SFOA was investigated using the year-long data set where concentrations were greatest in the autumn and winter. During the summer, SFOA contributed 11% to the organic fraction, where emissions resulted from different anthropogenic activities such as barbecues and domestic garden wood burning. The significant contribution of SFOA to total organic mass throughout the year suggests that the negative effects on health and air quality, as well as climate, are not just confined to winter as exposure to these aerosols and the associated black carbon can also occur during the summer, which may have significant implications for air-quality policies and mitigation strategies.

Airborne measurements of biomass burning organic aerosol (BBOA) from boreal forest fires reveal highly contrasting properties for plumes of different ages. These measurements, performed using an Aerodyne Research Inc. compact time-of-flight aerosol mass spectrometer (C-ToF-AMS) during the BORTAS (quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites) experiment in the summer of 2011, have been used to derive normalised excess organic aerosol (OA) mass concentrations (ΔOA / ΔCO), with higher average ratios observed closer to source (0.190±0.010) than in the far-field (0.097±0.002). The difference in ΔOA / ΔCO between fresh and aged plumes is influenced by a change in dominant combustion conditions throughout the campaign. Measurements at source comprised 3 plume interceptions during a single research flight and sampled largely smouldering fires. Twenty-three interceptions were made across four flights in the far-field, with plumes originating from fires occurring earlier in the campaign when fire activity had been more intense, creating an underlying contrast in emissions prior to any transformations associated with aging. Changing combustion conditions also affect the vertical distribution of biomass burning emissions, as aged plumes from more flaming-dominated fires are injected to higher altitudes of up to 6000 m. Proportional contributions of the mass-to-charge ratio (m/z) 60 and 44 peaks in the AMS mass spectra to the total OA mass (denoted f60 and f44) are used as tracers for primary and oxidised BBOA, respectively. f44 is lower on average in near-field plumes than those sampled in the far-field, in accordance with longer aging times as plumes are transported a greater distance from source. However, high levels of ΔO3 / ΔCO and −log(NOx / NOy) close to source indicate that emissions can be subject to very rapid oxidation over short timescales. Conversely, the lofting of plumes into the upper troposphere can lead to the retention of source profiles after transportation over extensive temporal and spatial scales, with f60 also higher on average in aged plumes. Evolution of OA composition with aging is comparable to observations of BB tracers in previous studies, revealing a consistent progression from f60 to f44. The elevated levels of oxygenation in aged plumes, and their association with lower average ΔOA / ΔCO, are consistent with OA loss through evaporation during aging due to a combination of dilution and chemical processing, while differences in combustion conditions throughout the campaign also have a significant influence on BBOA production and composition.

We used eddy covariance and meteorological measurements to estimate net ecosystem exchange of CO2 (NEE), gross ecosystem production (GEP), evapotranspiration (Et), and ecosystem water use efficiency (WUEe; calculated as GEP / Et during dry canopy conditions) in three upland forests in the New Jersey Pinelands, USA, that were defoliated by gypsy moth (Lymantria dispar L.) or burned using prescribed fire. Before disturbance, half-hourly daytime NEE during full sunlight conditions, daily GEP, and daily WUEe during the summer months were greater at the oak-dominated stand compared to the mixed or pine-dominated stands. Both defoliation by gypsy moth and prescribed burning reduced stand leaf area and nitrogen mass in foliage. During complete defoliation in 2007 at the oak stand, NEE during full sunlight conditions and daily GEP during the summer averaged only 14 and 35% of pre-disturbance values. Midday NEE and daily GEP then averaged 58 and 85%, and 71 and 78% of pre-defoliation values 1 and 2 years following complete defoliation, respectively. Prescribed fires conducted in the dormant season at the mixed and pine-dominated stands reduced NEE during full sunlight conditions and daily GEP during the following summer to 57 and 68%, and 79 and 82% of pre-disturbance values, respectively. Daily GEP during the summer was a strong function of N mass in foliage at the oak and mixed stands, but a weaker function of N in foliage at the pine-dominated stand. Ecosystem WUEe during the summer at the oak and mixed stands during defoliation by gypsy moth averaged 1.6 and 1.1 g C kg H2O−1, representing 60 and 46% of pre-disturbance values. In contrast, prescribed fires at the mixed and pine-dominated stands had little effect on WUEe. Two years following complete defoliation by gypsy moth, WUEe during the summer averaged 2.1 g C kg H2O−1, 80% of pre-disturbance values. WUEe was correlated with canopy N content only at the oak-dominated stand. Overall, our results indicate that WUEe during and following non-stand replacing disturbance is dependent on both the type and time since disturbance.

Airborne and ground-based measurements of methane (CH4), carbon dioxide (CO2) and boundary layer thermodynamics were recorded over the Fennoscandian landscape (67–69.5° N, 20–28° E) in July 2012 as part of the MAMM (Methane and other greenhouse gases in the Arctic: Measurements, process studies and Modelling) field campaign. Employing these airborne measurements and a simple boundary layer box model, net regional-scale (~ 100 km) fluxes were calculated to be 1.2 ± 0.5 mg CH4 h−1 m−2 and −350 ± 143 mg CO2 h−1 m−2. These airborne fluxes were found to be relatively consistent with seasonally averaged surface chamber (1.3 ± 1.0 mg CH4 h−1 m−2) and eddy covariance (1.3 ± 0.3 mg CH4 h−1 m−2 and −309 ± 306 mg CO2 h−1 m−2) flux measurements in the local area. The internal consistency of the aircraft-derived fluxes across a wide swath of Fennoscandia coupled with an excellent statistical comparison with local seasonally averaged ground-based measurements demonstrates the potential scalability of such localised measurements to regional-scale representativeness. Comparisons were also made to longer-term regional CH4 climatologies from the JULES (Joint UK Land Environment Simulator) and HYBRID8 land surface models within the area of the MAMM campaign. The average hourly emission flux output for the summer period (July–August) for the year 2012 was 0.084 mg CH4 h−1 m−2 (minimum 0.0 and maximum 0.21 mg CH4 h−1 m−2) for the JULES model and 0.088 mg CH4 h−1 m−2 (minimum 0.0008 and maximum 1.53 mg CH4 h−1 m−2) for HYBRID8. Based on these observations both models were found to significantly underestimate the CH4 emission flux in this region, which was linked to the under-prediction of the wetland extents generated by the models.

This study validates trace gas and thermodynamic retrievals from nadir infrared spectroscopic measurements recorded by the UK Met Office Airborne Research Interferometer Evaluation System (ARIES) – a thermal infrared, Fourier transform spectrometer (TIR-FTS) on the UK Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft. Trace-gas-concentration and thermodynamic profiles have been retrieved and validated for this study throughout the troposphere and planetary boundary layer (PBL) over a range of environmental variability using data from aircraft campaigns over and around London, the US Gulf Coast, and the Arctic Circle during the Clear air for London (ClearfLo), Joint Airborne IASI (Infrared Atmospheric Sounding Interferometer) Validation Experiment (JAIVEx), and Measurements, process studies, and Modelling (MAMM) aircraft campaigns, respectively. Vertically resolved retrievals of temperature and water vapour (H2O), and partial-column retrievals of methane (CH4), carbon monoxide (CO), and ozone (O3) (over both land and sea) were compared to corresponding measurements from high-precision in situ analysers and dropsondes operated on the FAAM aircraft. Average degrees of freedom for signal (DOFS) over a 0–9 km column range were found to be 4.97, 3.11, 0.91, 1.10, and 1.62 for temperature, H2O, CH4, CO, and O3, respectively, when retrieved on 10 vertical levels. Partial-column mean biases (and bias standard error) between the surface and ~ 9 km, when averaged across all flight campaigns, were found to be −0.7(±0.3) K, −479(±56) ppm, −11(±2) ppb, −3.3(±1.0) ppb, and +3.5(±1.0) ppb, respectively, whilst the typical a posteriori (total) uncertainties for individually retrieved profiles were 0.4, 9.5, 5.0, 21.2, and 15.0 %, respectively. Averaging kernels (AKs) derived for progressively lower altitudes show improving sensitivity to lower atmospheric layers when flying at lower altitudes. Temperature and H2O display significant vertically resolved sensitivity throughout the column, whilst trace gases are usefully retrieved only as partial-column quantities, with maximal sensitivity for trace gases other than H2O within a layer 1 and 2 km below the aircraft. This study demonstrates the valuable atmospheric composition information content that can be obtained by ARIES nadir TIR remote sensing for atmospheric process studies.

Black carbon aerosols (BC) at a London urban site were characterised in both winter- and summertime 2012 during the Clean Air for London (ClearfLo) project. Positive matrix factorisation (PMF) factors of organic aerosol mass spectra measured by a high-resolution aerosol mass spectrometer (HR-AMS) showed traffic-dominant sources in summer but in winter the influence of additional non-traffic sources became more important, mainly from solid fuel sources (SF). Measurements using a single particle soot photometer (SP2, DMT), showed the traffic-dominant BC exhibited an almost uniform BC core size (Dc) distribution with very thin coating thickness throughout the detectable range of Dc. However, the size distribution of sf (project average mass median Dc = 149 ± 22 nm in winter, and 120 ± 6 nm in summer) and BC coating thickness varied significantly in winter. A novel methodology was developed to attribute the BC number concentrations and mass abundances from traffic (BCtr) and from SF (BCsf), by using a 2-D histogram of the particle optical properties as a function of BC core size, as measured by the SP2. The BCtr and BCsf showed distinctly different sf distributions and coating thicknesses, with BCsf displaying larger Dc and larger coating thickness compared to BCtr. BC particles from different sources were also apportioned by applying a multiple linear regression between the total BC mass and each AMS-PMF factor (BC–AMS–PMF method), and also attributed by applying the absorption spectral dependence of carbonaceous aerosols to 7-wavelength Aethalometer measurements (Aethalometer method). Air masses that originated from westerly (W), southeasterly (SE), and easterly (E) sectors showed BCsf fractions that ranged from low to high, and whose mass median Dc values were 137 ± 10 nm, 143 ± 11 nm and 169 ± 29 nm, respectively. The corresponding bulk relative coating thickness of BC (coated particle size/BC core – Dp/Dc) for these same sectors was 1.28 ± 0.07, 1.45 ± 0.16 and 1.65 ± 0.19. For W, SE and E air masses, the number fraction of BCsf ranged from 6 ± 2% to 11 ± 5% to 18 ± 10%, respectively, but importantly the larger BC core sizes lead to an increased fraction of BCsf in terms of mass than number (for W, SE and E air masses, the BCsf mass fractions ranged from 16 ± 6%, 24 ± 10% and 39 ± 14%, respectively). An increased fraction of non-BC particles (particles that did not contain a BC core) was also observed when SF sources were more significant. The BC mass attribution by the SP2 method agreed well with the BC–AMS–PMF multiple linear regression method (BC–AMS–PMF : SP2 ratio = 1.05, r2 = 0.80) over the entire experimental period. Good agreement was found between BCsf attributed with the Aethalometer model and the SP2. However, the assumed absorption Ångström exponent (αwb) had to be changed according to the different air mass sectors to yield the best comparison with the SP2. This could be due to influences of fuel type or burn phase.

The behaviour of primary biological aerosols (PBAs) at an elevated, un-polluted North American forest site was studied using an ultra violet-light induced fluorescence (UV-LIF) measurement technique in conjunction with hierarchical agglomerative cluster analysis (HA-CA). Contemporaneous UV-LIF measurements were made with two wide-band integrated bioaerosol spectrometers, WIBS-3 and WIBS-4, which sampled close to the forest floor and via a continuous vertical profiling system, respectively. Additionally, meteorological parameters were recorded at various heights throughout the forest and used to estimate PBAP (Primary Biological Aerosol Particle) fluxes. HA-CA using data from the two, physically separated WIBS instruments independently yielded very similar cluster solutions. All fluorescent clusters displayed a diurnal minimum at midday at the forest floor with maximum concentration occurring at night. Additionally, the number concentration of each fluorescent cluster was enhanced, to different degrees, during wet periods. A cluster that displayed the greatest enhancement and highest concentration during sustained wet periods appears consistent with behaviour reported for fungal spores. A cluster that appears to be behaviourally consistent with bacteria dominated during dry periods. Fluorescent particle concentrations were found to be greater within the forest canopy than at the forest floor, indicating that the canopy was the main source of these particles rather than the minimal surface vegetation, which appeared to contribute little to overall PBA concentrations at this site. Fluorescent particle concentration was positively correlated with relative humidity (RH), and parameterisations of the aerosol response during dry and wet periods are reported. The aforementioned fungal spore-like cluster displayed a strong positive response to increasing RH. The bacteria-like cluster responded more strongly to direct rain-fall events than other PBA types. Peak concentrations of this cluster are shown to be linearly correlated to the log of peak rainfall rates. Parallel studies by Huffman et al. (2013) and Prenni et al. (2013) showed that the fluorescent particle concentrations correlated linearly with ice nuclei (IN) concentrations at this site during rain events. We discuss this result in conjunction with our cluster analysis to appraise the candidate IN.

In situ airborne measurements were made over eastern Canada in summer 2011 as part of the BORTAS experiment (Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites). In this paper we present observations of greenhouse gases (CO2 and CH4) and other biomass burning tracers (CO, HCN and CH3CN), both climatologically and through case studies, as recorded on board the FAAM BAe-146 research aircraft. Vertical profiles of CO2 were generally characterised by depleted boundary layer concentrations relative to the free troposphere, consistent with terrestrial biospheric uptake. In contrast, CH4 concentrations were found to rise with decreasing altitude due to strong local and regional surface sources. BORTAS observations were found to be broadly comparable with both previous measurements in the region during the regional burning season and with reanalysed composition fields from the EU Monitoring Atmospheric Composition and Change (MACC) project. We use coincident tracer–tracer correlations and a Lagrangian trajectory model to characterise and differentiate air mass history of intercepted plumes. In particular, CO, HCN and CH3CN were used to identify air masses that have been recently influenced by biomass burning. Examining individual cases we were able to quantify emissions from biomass burning. Using both near-field (< 1 day) and far-field (> 1 day) sampling, boreal forest fire plumes were identified throughout the troposphere. Fresh plumes from fires in northwestern Ontario yield emission factors for CH4 and CO2 of 8.5 ± 0.9 g (kg dry matter)−1 and 1512 ± 185 g (kg dry matter)−1, respectively. We have also investigated the efficacy of calculating emission factors from far-field sampling, in which there might be expected to be limited mixing with background and other characteristic air masses, and we provide guidance on best practice and limitations in such analysis. We have found that for measurements within plumes that originated from fires in northwestern Ontario 2–4 days upwind, emission factors can be calculated that range between 1618 ± 216 and 1702 ± 173 g (kg dry matter)−1 for CO2 and 1.8 ± 0.2 and 6.1 ± 1 g (kg dry matter)−1 for CH4.

Total bacteria, fungal spore and yeast counts were compared with ultraviolet-light-induced fluorescence (UV-LIF) measurements of ambient aerosol at the summit of the Puy de Dôme (PdD) mountain in central France (1465 m a.s.l), which represents a background elevated site. Bacteria, fungal spores and yeast were enumerated by epifluorescence microscopy (EFM) and found to number 2.2 to 23 L−1 and 0.8 to 2 L−1, respectively. Bacteria counts on two successive nights were an order of magnitude larger than in the intervening day. A wide issue bioaerosol spectrometer, version 3 (WIBS-3) was used to perform UV-LIF measurements on ambient aerosol sized 0.8 to 20 μm. Mean total number concentration was 270 L−1 (σ = 66 L−1), found predominantly in a size mode at 2 μm for most of the campaign. Total concentration (fluorescent + non-fluorescent aerosol) peaked at 500 L−1 with a size mode at 1 μm because of a change in air mass origin lasting around 48 h. The WIBS-3 features two excitation and fluorescence detection wavelengths corresponding to different biological molecules, although non-biological interferents also contribute. The mean fluorescent particle concentration after short-wave (280 nm; associated with tryptophan) excitation was 12 L−1 (σ = 6 L−1), and did not vary much throughout the campaign. In contrast, the mean concentration of particles fluorescent after long-wave (370 nm; associated with NADH) excitation was 95 L−1 (σ = 25 L−1), and a nightly rise and subsequent fall of up to 100 L−1 formed a strong diurnal cycle in the latter. The two fluorescent populations exhibited size modes at 3 μm and 2 to 3 μm, respectively. A hierarchical agglomerative cluster analysis algorithm was applied to the data and used to extract different particle factors. A cluster concentration time series representative of bacteria was identified. This was found to exhibit a diurnal cycle with a maximum peak appearing during the day. Analysis of organic mass spectra recorded using an aerosol mass spectrometer (AMS; Aerodyne Inc.) suggests that aerosol reaching the site at night was more aged than that during the day, indicative of sampling the residual layer at night. Supplementary meteorological data and previous work also show that PdD lies in the residual layer/free troposphere at night, and this is thought to cause the observed diurnal cycles in organic-type and fluorescent aerosol particles. Based on the observed disparity between bacteria and fluorescent particle concentrations, fluorescent non-PBA is likely to be important in the WIBS-3 data and the surprisingly high fluorescent concentration in the residual layer/free troposphere raises questions about a ubiquitous background in continental air during the summer.

High-resolution CH4 and CO2 measurements were made on board the FAAM BAe-146 UK (Facility for Airborne Atmospheric Measurements, British Aerospace-146) atmospheric research aircraft during a number of field campaigns. The system was based on an infrared spectrometer using the cavity-enhanced absorption spectroscopy technique. Correction functions to convert the mole fractions retrieved from the spectroscopy to dry-air mole fractions were derived using laboratory experiments and over a 3 month period showed good stability. Long-term performance of the system was monitored using WMO (World Meteorological Office) traceable calibration gases. During the first year of operation (29 flights) analysis of the system's in-flight calibrations suggest that its measurements are accurate to 1.28 ppb (1σ repeatability at 1 Hz = 2.48 ppb) for CH4 and 0.17 ppm (1σ repeatability at 1 Hz = 0.66 ppm) for CO2. The system was found to be robust, no major motion or altitude dependency could be detected in the measurements. An inter-comparison between whole-air samples that were analysed post-flight for CH4 and CO2 by cavity ring-down spectroscopy showed a mean difference between the two techniques of −2.4 ppb (1σ = 2.3 ppb) for CH4 and −0.22 ppm (1σ = 0.45 ppm) for CO2. In September 2012, the system was used to sample biomass-burning plumes in Brazil as part of the SAMBBA project (South AMerican Biomass Burning Analysis). From these and simultaneous CO measurements, emission factors for savannah fires were calculated. These were found to be 2.2 ± 0.2 g (kg dry matter)−1 for CH4 and 1710 ± 171 g (kg dry matter)−1 for CO2, which are in excellent agreement with previous estimates in the literature.

Simultaneous measurements of changes in phytoplankton biomass and the metal and phosphorus (P) content of cells have been captured to attest to metal to P stoichiometries for freshwater phytoplankton. Three Scottish lakes that had received high, medium or low metal contamination from the atmosphere were selected for study. Phytoplankton cells were collected and Inductively Coupled Plasma-Mass Spectrometry was used to measure their lead (Pb), cadmium (Cd), mercury (Hg), copper (Cu), zinc (Zn), nickel (Ni), chromium (Cr), manganese (Mn), cobalt (Co) and P content. Increased phytoplankton growth in the lakes resulted in significant algae growth dilution of the mass-specific Pb, Cd, Hg, Cu, Ni and Cr in the phytoplankton. Changes in the phytoplankton cell count and their Hg, Pb, Cd, Cu, Mn, Co, Ni and Cr concentrations showed the process of algae bloom dilution to be subject to exponential decay, which accelerated in the order of Mn

In-situ aircraft observations of ice crystal concentrations in Antarctic clouds are presented for the first time. Orographic, layer and wave clouds around the Antarctic Peninsula and Larsen Ice shelf regions were penetrated by the British Antarctic Survey's Twin Otter aircraft, which was equipped with modern cloud physics probes. The clouds studied were mostly in the free troposphere and hence ice crystals blown from the surface are unlikely to have been a major source for the ice phase. The temperature range covered by the experiments was 0 to −21 °C. The clouds were found to contain supercooled liquid water in most regions and at heterogeneous ice formation temperatures ice crystal concentrations (60 s averages) were often less than 0.07 l−1, although values up to 0.22 l−1 were observed. Estimates of observed aerosol concentrations were used as input into the DeMott et al. (2010) ice nuclei (IN) parameterisation. The observed ice crystal number concentrations were generally in broad agreement with the IN predictions, although on the whole the predicted values were higher. Possible reasons for this are discussed and include the lack of IN observations in this region with which to characterise the parameterisation, and/or problems in relating ice concentration measurements to IN concentrations. Other IN parameterisations significantly overestimated the number of ice particles. Generally ice particle concentrations were much lower than found in clouds in middle latitudes for a given temperature. Higher ice crystal concentrations were sometimes observed at temperatures warmer than −9 °C, with values of several per litre reached. These were attributable to secondary ice particle production by the Hallett Mossop process. Even in this temperature range it was observed that there were regions with little or no ice that were dominated by supercooled liquid water. It is likely that in some cases this was due to a lack of seeding ice crystals to act as rimers to initiate secondary ice particle production. This highlights the chaotic and spatially inhomogeneous nature of this process and indicates that the accurate representation of it in global models is likely to represent a challenge. However, the contrast between Hallett Mossop zone ice concentrations and the fairly low concentrations of heterogeneously nucleated ice suggests that the Hallet Mossop process has the potential to be very important in remote, pristine regions such as around the Antarctic coast.

Contrails and especially their evolution into cirrus-like clouds are thought to have very important effects on local and global radiation budgets, though are generally not well represented in global climate models. Lack of contrail parameterisations is due to the limited availability of in situ contrail measurements which are difficult to obtain. Here we present a methodology for successful sampling and interpretation of contrail microphysical and radiative data using both in situ and remote sensing instrumentation on board the FAAM BAe146 UK research aircraft as part of the COntrails Spreading Into Cirrus (COSIC) study. Forecast models were utilised to determine flight regions suitable for contrail formation and sampling; regions that were both free of cloud but showed a high probability of occurrence of air mass being supersaturated with respect to ice. The FAAM research aircraft, fitted with cloud microphysics probes and remote sensing instruments, formed a distinctive spiral-shaped contrail in the predicted area by flying in an orbit over the same ground position as the wind advected the contrails to the east. Parts of these contrails were sampled during the completion of four orbits, with sampled contrail regions being between 7 and 30 min old. Lidar measurements were useful for in-flight determination of the location and spatial extent of the contrails, and also to report extinction values that agreed well with those calculated from the microphysical data. A shortwave spectrometer was also able to detect the contrails, though the signal was weak due to the dispersion and evaporation of the contrails. Post-flight the UK Met Office NAME III dispersion model was successfully used as a tool for modelling the dispersion of the persistent contrail; determining its location and age, and determining when there was interference from other measured aircraft contrails or when cirrus encroached on the area later in the flight. The persistent contrails were found to consist of small (~10 μm) plate-like crystals where growth of ice crystals to larger sizes (~100 μm) was typically detected when higher water vapour levels were present. Using the cloud microphysics data, extinction co-efficient values were calculated and found to be 0.01–1 km−1. The contrails formed during the flight (referred to as B587) were found to have a visible lifetime of ~40 min, and limited water vapour supply was thought to have suppressed ice crystal growth.

Aircraft measurements of the microphysics of a tropical convective anvil (at temperatures ~−60 °C) forming above the Hector storm, over the Tiwi Islands, Northern Australia, have been conducted with a view to determining ice crystal aggregation efficiencies from in situ measurements. The observed microphysics have been compared to an explicit bin-microphysical model of the anvil region, which includes crystal growth by vapour diffusion and aggregation and the process of differential sedimentation. It has been found in flights made using straight and level runs perpendicular to the storm that the number of ice crystals initially decreased with distance from the storm as aggregation took place resulting in larger crystals, followed by their loss from the cloud layer due to sedimentation. The net result was that the mass (i.e. Ice Water Content) in the anvil Ci cloud decreased, but also that the average particle size (weighted by number) remained relatively constant along the length of the anvil outflow. Comparisons with the explicit microphysics model showed that the changes in the shapes of the ice crystal spectra as a function of distance from the storm could be explained by the model if the aggregation efficiency was set to values of Eagg~0.5 and higher. This result is supported by recent literature on aggregation efficiencies for complex ice particles and suggests that either the mechanism of particle interlocking is important to the aggregation process, or that other effects are occuring, such as enhancement of ice-aggregation by high electric fields that arise as a consequence of charge separation within the storm. It is noteworthy that this value of the ice crystal aggregation efficiency is much larger than values used in cloud resolving models at these temperatures, which typically use E~0.0016. These results are important to understanding how cold clouds evolve in time and for the treatment of the evolution of tropical Ci in numerical models.