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Organic compounds represent a significant fraction of submicrometer atmospheric aerosol mass. Even if most of these compounds are semi-volatile in atmospheric concentrations, the ambient organic aerosol volatility is quite uncertain. The most common volatility measurement method relies on the use of a thermodenuder (TD). The aerosol passes through a heated tube where its more volatile components evaporate, leaving the less volatile components behind in the particulate phase. The typical result of a thermodenuder measurement is the mass fraction remaining (MFR), which depends, among other factors, on the organic aerosol (OA) vaporization enthalpy and the accommodation coefficient. We use a new method combining forward modeling, introduction of "experimental" error, and inverse modeling with error minimization for the interpretation of TD measurements. The OA volatility distribution, its effective vaporization enthalpy, the mass accommodation coefficient and the corresponding uncertainty ranges are calculated. Our results indicate that existing TD-based approaches quite often cannot estimate reliably the OA volatility distribution, leading to large uncertainties, since there are many different combinations of the three properties that can lead to similar thermograms. We propose an improved experimental approach combining TD and isothermal dilution measurements. We evaluate this experimental approach using the same model, and show that it is suitable for studies of OA volatility in the lab and the field.

Global climate model (GCM) outputs feature systematic biases that render them unsuitable for direct use by impact models, especially for hydrological studies. To deal with this issue, many bias correction techniques have been developed to adjust the modelled variables against observations, focusing mainly on precipitation and temperature. However, most state-of-the-art hydrological models require more forcing variables, in addition to precipitation and temperature, such as radiation, humidity, air pressure, and wind speed. The biases in these additional variables can hinder hydrological simulations, but the effect of the bias of each variable is unexplored. Here we examine the effect of GCM biases on historical runoff simulations for each forcing variable individually, using the JULES land surface model set up at the global scale. Based on the quantified effect, we assess which variables should be included in bias correction procedures. To this end, a partial correction bias assessment experiment is conducted, to test the effect of the biases of six climate variables from a set of three GCMs. The effect of the bias of each climate variable individually is quantified by comparing the changes in simulated runoff that correspond to the bias of each tested variable. A methodology for the classification of the effect of biases in four effect categories (ECs), based on the magnitude and sensitivity of runoff changes, is developed and applied. Our results show that, while globally the largest changes in modelled runoff are caused by precipitation and temperature biases, there are regions where runoff is substantially affected by and/or more sensitive to radiation and humidity. Global maps of bias ECs reveal the regions mostly affected by the bias of each variable. Based on our findings, for global-scale applications, bias correction of radiation and humidity, in addition to that of precipitation and temperature, is advised. Finer spatial-scale information is also provided, to suggest bias correction of variables beyond precipitation and temperature for regional studies.

In this paper we provide an overview of new knowledge on oxygen depletion (hypoxia) and related phenomena in aquatic systems resulting from the EU-FP7 project HYPOX ("In situ monitoring of oxygen depletion in hypoxic ecosystems of coastal and open seas, and landlocked water bodies", http://www.hypox.net). In view of the anticipated oxygen loss in aquatic systems due to eutrophication and climate change, HYPOX was set up to improve capacities to monitor hypoxia as well as to understand its causes and consequences. Temporal dynamics and spatial patterns of hypoxia were analyzed in field studies in various aquatic environments, including the Baltic Sea, the Black Sea, Scottish and Scandinavian fjords, Ionian Sea lagoons and embayments, and Swiss lakes. Examples of episodic and rapid (hours) occurrences of hypoxia, as well as seasonal changes in bottom-water oxygenation in stratified systems, are discussed. Geologically driven hypoxia caused by gas seepage is demonstrated. Using novel technologies, temporal and spatial patterns of water-column oxygenation, from basin-scale seasonal patterns to meter-scale sub-micromolar oxygen distributions, were resolved. Existing multidecadal monitoring data were used to demonstrate the imprint of climate change and eutrophication on long-term oxygen distributions. Organic and inorganic proxies were used to extend investigations on past oxygen conditions to centennial and even longer timescales that cannot be resolved by monitoring. The effects of hypoxia on faunal communities and biogeochemical processes were also addressed in the project. An investigation of benthic fauna is presented as an example of hypoxia-devastated benthic communities that slowly recover upon a reduction in eutrophication in a system where naturally occurring hypoxia overlaps with anthropogenic hypoxia. Biogeochemical investigations reveal that oxygen intrusions have a strong effect on the microbially mediated redox cycling of elements. Observations and modeling studies of the sediments demonstrate the effect of seasonally changing oxygen conditions on benthic mineralization pathways and fluxes. Data quality and access are crucial in hypoxia research. Technical issues are therefore also addressed, including the availability of suitable sensor technology to resolve the gradual changes in bottom-water oxygen in marine systems that can be expected as a result of climate change. Using cabled observatories as examples, we show how the benefit of continuous oxygen monitoring can be maximized by adopting proper quality control. Finally, we discuss strategies for state-of-the-art data archiving and dissemination in compliance with global standards, and how ocean observations can contribute to global earth observation attempts.

The ability of chemical transport model (CTM) PMCAMx to reproduce aerosol optical depth (AOD) measurements by the Aerosol Robotic Network (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) over Europe during the photochemically active period of May 2008 (EUCAARI campaign) is evaluated. Periods with high dust or sea-salt levels are excluded, so the analysis focuses on the ability of the model to simulate the mostly secondary aerosol and its interactions with water. PMCAMx reproduces the monthly mean MODIS and AERONET AOD values over the Iberian Peninsula, the British Isles, central Europe, and Russia with a fractional bias of less than 15 % and a fractional error of less than 30 %. However, the model overestimates the AOD over northern Europe, most probably due to an overestimation of organic aerosol and sulfates. At the other end, PMCAMx underestimates the monthly mean MODIS AOD over the Balkans, the Mediterranean, and the South Atlantic. These errors appear to be related to an underestimation of sulfates. Sensitivity tests indicate that the evaluation results of the monthly mean AODs are quite sensitive to the relative humidity (RH) fields used by PMCAMx, but are not sensitive to the simulated size distribution and the black carbon mixing state. The screening of the satellite retrievals for periods with high dust (or coarse particles in general) concentrations as well as the combination of the MODIS and AERONET datasets lead to more robust conclusions about the ability of the model to simulate the secondary aerosol components that dominate the AOD during this period.

The evolution of environmental changes during the last decades and the impact on the living biomass in the western part of Amvrakikos Gulf was investigated using abundances and species distributions of benthic foraminifera and lipid biomarker concentrations. These proxies indicated that the gulf has markedly changed due to eutrophication. Eutrophication has led to a higher productivity, a higher bacterial biomass, shifts towards opportunistic and tolerant benthic foraminifera species (e.g. Bulimina elongata, Nonionella turgida, Textularia agglutinans, Ammonia tepida) and a lower benthic species density. Close to the Preveza Strait (connection between the gulf and the Ionian Sea), the benthic assemblages were more diversified under more oxygenated conditions. Sea grass meadows largely contributed to the organic matter at this sampling site. The occurrence of isorenieratane, chlorobactane and lycopane supported by oxygen monitoring data indicated that anoxic (and partly euxinic) conditions prevailed seasonally throughout the western part of the gulf with more severe oxygen depletion towards the east. Increased surface water temperatures have led to a higher stratification, which reduced oxygen resupply to bottom waters. Altogether, these developments led to mass mortality events and ecosystem decline in Amvrakikos Gulf.

Smog chamber experiments using as a starting point ambient air can improve our understanding of the evolution of atmospheric particulate matter at timescales longer than those achieved by traditional laboratory experiments. These types of studies can take place under more realistic environmental conditions addressing the interactions among multiple pollutants. The use of two identical smog chambers, with the first serving as the baseline chamber and the second as the perturbation chamber (in which addition or removal of pollutants, addition of oxidants, change in the relative humidity, etc.), can facilitate the interpretation of the results in such inherently complex experiments. The differences of the measurements in the two chambers can be used as the basis for the analysis of the corresponding chemical or physical processes of ambient air. A portable dual smog chamber system was developed using two identical pillow-shaped smog chambers (1.5 m3 each). The two chambers are surrounded by UV lamps in a hexagonal arrangement yielding a total JNO2 of 0.1 min−1. The system can be easily disassembled and transported enabling the study of various atmospheric environments. Moreover, it can be used with natural sunlight. The results of test experiments using ambient air as starting point are discussed as examples of applications of this system.

Wind turbine rotors in idling operation mode can experience high angles of attack within the post-stall region that are capable of triggering stall-induced vibrations. The aim of the present paper is to extend the existing knowledge on the dynamics and aerodynamics of an idling wind turbine and characterize its stability. Rotor stability in slow idling operation is assessed on the basis of nonlinear time domain and linear eigenvalue analyses. The aim is to establish when linear analysis is reliable and identify cases for which nonlinear effects are significant. Analysis is performed for a 10 MW conceptual wind turbine designed by DTU. First, the flow conditions that are likely to favor stall-induced instabilities are identified through nonlinear time domain aeroelastic simulations. Next, for the above specified conditions, eigenvalue stability analysis is performed to identify the low damped modes of the turbine. The eigenvalue stability results are evaluated through computations of the work done by the aerodynamic forces under imposed harmonic motion following the shape and frequency of the various modes. Nonlinear work characteristics predicted by the ONERA and Beddoes–Leishman (BL) dynamic stall models are compared. Both the eigenvalue and work analyses indicate that the asymmetric and symmetric out-of-plane modes have the lowest damping. The results of the eigenvalue analysis agree well with those of the nonlinear work analysis and the time domain simulations.

In this study, Algal Pigment Index 2 (API2) is investigated in Sagres, an area located in the Atlantic off the southwestern Iberian Peninsula. Standard results provided by the MEdium Resolution Image Spectrometer (MERIS) ocean colour sensor were compared with alternative data products, determined through a regional inversion scheme, using both MERIS and in situ remote sensing reflectances (Rrs) as input data. The reference quantity for performance assessment is in situ total chlorophyll a (TChl a) concentration estimated through a phytoplankton absorption coefficient (i.e. equivalent to API2). Additional comparison of data products has also been addressed for TChl a concentration determined by high-performance liquid chromatography. The MERIS matchup analysis revealed a systematic underestimation of TChl a, which was confirmed with an independent comparison of product map analysis. The study demonstrates the importance of regional algorithms for the study area that could complement upcoming standard results of the current Sentinel-3/OLCI space mission.

Measurements of the status and trends of key indicators for the ocean and marine life are required to inform policy and management in the context of growing human uses of marine resources, coastal development, and climate change. Two synergistic efforts identify specific priority variables for monitoring: Essential Ocean Variables (EOVs) through the Global Ocean Observing System (GOOS), and Essential Biodiversity Variables (EBVs) from the Group on Earth Observations Biodiversity Observation Network (GEO BON) (see Data Sheet 1 in Supplementary Materials for a glossary of acronyms). Both systems support reporting against internationally agreed conventions and treaties. GOOS, established under the auspices of the Intergovernmental Oceanographic Commission (IOC), plays a leading role in coordinating global monitoring of the ocean and in the definition of EOVs. GEO BON is a global biodiversity observation network that coordinates observations to enhance management of the world’s biodiversity and promote both the awareness and accounting of ecosystem services. Convergence and agreement between these two efforts are required to streamline existing and new marine observation programs to advance scientific knowledge effectively and to support the sustainable use and management of ocean spaces and resources. In this context, the Marine Biodiversity Observation Network (MBON), a thematic component of GEO BON, is collaborating with GOOS, the Ocean Biogeographic Information System (OBIS), and the Integrated Marine Biosphere Research (IMBeR) project to ensure that EBVs and EOVs are complementary, representing alternative uses of a common set of scientific measurements. This work is informed by the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM), an intergovernmental body of technical experts that helps international coordination on best practices for observing, data management and services, combined with capacity development expertise. Characterizing biodiversity and understanding its drivers will require incorporation of observations fromtraditional andmolecular taxonomy, animal tagging and tracking efforts, ocean biogeochemistry, and ocean observatory initiatives including the deep ocean and seafloor. The partnership between large-scale ocean observing and product distribution initiatives (MBON, OBIS, JCOMM, and GOOS) is an expedited, effective way to support international policy-level assessments (e.g., the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services or IPBES), along with the implementation of international development goals (e.g., the United Nations Sustainable Development Goals). Refereed 14 Manual (incl. handbook, guide, cookbook etc) 2018-06-27

PMCAMx-UF, a three-dimensional chemical transport model focusing on the simulation of the ultrafine particle size distribution and composition has been extended with the addition of the volatility basis set (VBS) approach for the simulation of organic aerosol (OA). The model was applied in Europe to quantify the effect of secondary semi-volatile organic vapors on particle number concentrations. The model predictions were evaluated against field observations collected during the PEGASOS 2012 campaign. The measurements included both ground and airborne measurements, from stations across Europe and a zeppelin measuring above Po Valley. The ground level concentrations of particles with a diameter larger than 100 nm (N100) were reproduced with a daily normalized mean error of 40 % and a daily normalized mean bias of −20 %. PMCAMx-UF tended to overestimate the concentration of particles with a diameter larger than 10 nm (N10) with a daily normalized mean bias of 75 %. The model was able to reproduce, within a factor of 2, 85 % of the N10 and 75 % of the N100 zeppelin measurements above ground. The condensation of organics led to an increase (50 %–120 %) in the N100 concentration mainly in central and northern Europe, while the N10 concentration decreased by 10 %–30 %. Including the VBS in PMCAMx-UF improved its ability to simulate aerosol number concentration compared to simulations neglecting organic condensation on ultrafine particles.