Search

Engaging students in science and helping them develop an understanding of its ideas has been a consistent challenge for both science teachers and science educators alike. Such a challenge is even greater in the context of the “Science for All” curriculum initiative. However, Bruner's notion of “narrative thinking” and Egan's “romantic understanding” offer an alternative approach to teaching and learning science, in a way that engagement and understanding become a possibility. This chapter focuses on students' “narrative mode of thought,” as a bridge to understanding science—which has traditionally been based more upon the use of logico-mathematical thinking in the upper grades—and on a distinctive form of understanding the world, characteristic of students of the age range from 8 to 15 years. This latter form of understanding, that the educational theorist Kieran Egan calls “romantic understanding,” has features that can be readily associated with the natural world and its phenomena. Therefore its development could be fostered in the context of school science learning, and in a way that the narrative mode would also be taken into consideration.

Background: In the recent years clinical ethics consultations (CEC) received an increasing attention not only in patients with medical conditions but also in those with mental disorders. However, the systematic and empirical knowledge is still small. The aim of this observational study was to investigate whether CECs differ between psychiatric and medical hospital inpatients regarding ethical issues, goals, characteristics, processes, and outcomes. Methods: This is a retrospective and in parts prospective analysis of a semi-structured CEC approach provided by the CEC service at a large German general hospital between January 2006 and June 2015. Results: A total of 259 CECs in three inpatient settings were investigated, i.e. intensive care units (ICU, 43.6%), low care units (LCU, 33.6%), and psychiatric care units (PCU, 22.8%). In all groups, most ethical issues addressed treatment intensity (80.6%) and resulted in over 93% in participants' agreement on final ethical recommendations as well as in high implementation rates (>89%). However, we found significant group differences: In PCUs patients participated more often in the CEC (p < .001), the number of all participants was higher (p < .001), CECs were more time expensive (p < .001), and more recommendations focused on interventions against the patients' declared intention (37.7% versus 0%) than in the other groups. Discussion: In spite of different clinical characteristics and ethical issues between patients and settings, consensus and implementation of the CEC recommendation could be achieved at a high rate in all groups. There are substantial differences regarding goals, participation of patients, and processes. It is worth considering adapting the CEC to the special needs in psychiatric settings, especially under the aspect of the patients' perspective and involvement.

Vaginal colonization with Ureaplasma (U.) spp. has been shown to be associated with adverse pregnancy outcome; however, data on neonatal outcome are scarce. The aim of the study was to investigate whether maternal vaginal colonization with U. spp. in early pregnancy represents a risk factor for adverse short- or long-term outcome of preterm infants. Previously, 4330 pregnant women were enrolled in an observational multicenter study, analyzing the association between vaginal U. spp. colonization and spontaneous preterm birth. U. spp. colonization was diagnosed via PCR analysis from vaginal swabs. For this study, data on short-term outcome were collected from medical records and long-term outcome was examined via Bayley Scales of Infant Development at 24 months adjusted age. Two-hundred-and-thirty-eight children were born U. spp. colonization and severe intraventricular hemorrhage (10.4% vs. 2.6%, p = 0.03), retinopathy of prematurity (21.7% vs. 10.3%, p = 0.03), and adverse psychomotor outcome (24.3% vs. 1.8%, OR 13.154, 95%CI 1.6,110.2, p = 0.005). The data suggest an association between vaginal U. spp. colonization in early pregnancy and adverse short- and long-term outcome of very preterm infants.

In the Hemispheric Transport of Air Pollution Phase 2 (HTAP2) exercise, a range of global atmospheric general circulation and chemical transport models performed coordinated perturbation experiments with 20 % reductions in emissions of anthropogenic aerosols, or aerosol precursors, in a number of source regions. Here, we compare the resulting changes in the atmospheric load and vertically resolved profiles of black carbon (BC), organic aerosols (OA) and sulfate (SO4) from 10 models that include treatment of aerosols. We use a set of temporally, horizontally and vertically resolved profiles of aerosol forcing efficiency (AFE) to estimate the impact of emission changes in six major source regions on global radiative forcing (RF) pertaining to the direct aerosol effect, finding values between. 51.9 and 210.8 mW m−2 Tg−1 for BC, between −2.4 and −17.9 mW m−2 Tg−1 for OA and between −3.6 and −10.3 W m−2 Tg−1 for SO4. In most cases, the local influence dominates, but results show that mitigations in south and east Asia have substantial impacts on the radiative budget in all investigated receptor regions, especially for BC. In Russia and the Middle East, more than 80 % of the forcing for BC and OA is due to extra-regional emission reductions. Similarly, for North America, BC emissions control in east Asia is found to be more important than domestic mitigations, which is consistent with previous findings. Comparing fully resolved RF calculations to RF estimates based on vertically averaged AFE profiles allows us to quantify the importance of vertical resolution to RF estimates. We find that locally in the source regions, a 20 % emission reduction strengthens the radiative forcing associated with SO4 by 25 % when including the vertical dimension, as the AFE for SO4 is strongest near the surface. Conversely, the local RF from BC weakens by 37 % since BC AFE is low close to the ground. The fraction of BC direct effect forcing attributable to intercontinental transport, on the other hand, is enhanced by one-third when accounting for the vertical aspect, because long-range transport primarily leads to aerosol changes at high altitudes, where the BC AFE is strong. While the surface temperature response may vary with the altitude of aerosol change, the analysis in the present study is not extended to estimates of temperature or precipitation changes.

Numerical simulations provide a considerable aid in studying past climates. Out of the various approaches taken in designing numerical climate experiments, transient simulations have been found to be the most optimal when it comes to comparison with proxy data. However, multi-millennial or longer simulations using fully coupled general circulation models are computationally very expensive such that acceleration techniques are frequently applied. In this study, we compare the results from transient simulations of the present and the last interglacial with and without acceleration of the orbital forcing, using the comprehensive coupled climate model CCSM3 (Community Climate System Model version 3). Our study shows that in low-latitude regions, the simulation of long-term variations in interglacial surface climate is not significantly affected by the use of the acceleration technique (with an acceleration factor of 10) and hence, large-scale model–data comparison of surface variables is not hampered. However, in high-latitude regions where the surface climate has a direct connection to the deep ocean, e.g. in the Southern Ocean or the Nordic Seas, acceleration-induced biases in sea-surface temperature evolution may occur with potential influence on the dynamics of the overlying atmosphere.

The ability of seven state-of-the-art chemistry–aerosol models to reproduce distributions of tropospheric ozone and its precursors, as well as aerosols over eastern Asia in summer 2008, is evaluated. The study focuses on the performance of models used to assess impacts of pollutants on climate and air quality as part of the EU ECLIPSE project. Models, run using the same ECLIPSE emissions, are compared over different spatial scales to in situ surface, vertical profiles and satellite data. Several rather clear biases are found between model results and observations, including overestimation of ozone at rural locations downwind of the main emission regions in China, as well as downwind over the Pacific. Several models produce too much ozone over polluted regions, which is then transported downwind. Analysis points to different factors related to the ability of models to simulate VOC-limited regimes over polluted regions and NOx limited regimes downwind. This may also be linked to biases compared to satellite NO2, indicating overestimation of NO2 over and to the north of the northern China Plain emission region. On the other hand, model NO2 is too low to the south and west of this region and over South Korea/Japan. Overestimation of ozone is linked to systematic underestimation of CO particularly at rural sites and downwind of the main Chinese emission regions. This is likely to be due to enhanced destruction of CO by OH. Overestimation of Asian ozone and its transport downwind implies that radiative forcing from this source may be overestimated. Model-observation discrepancies over Beijing do not appear to be due to emission controls linked to the Olympic Games in summer 2008.With regard to aerosols, most models reproduce the satellite-derived AOD patterns over eastern China. Our study nevertheless reveals an overestimation of ECLIPSE model mean surface BC and sulphate aerosols in urban China in summer 2008. The effect of the short-term emission mitigation in Beijing is too weak to explain the differences between the models. Our results rather point to an overestimation of SO2 emissions, in particular, close to the surface in Chinese urban areas. However, we also identify a clear underestimation of aerosol concentrations over northern India, suggesting that the rapid recent growth of emissions in India, as well as their spatial extension, is underestimated in emission inventories. Model deficiencies in the representation of pollution accumulation due to the Indian monsoon may also be playing a role. Comparison with vertical aerosol lidar measurements highlights a general underestimation of scattering aerosols in the boundary layer associated with overestimation in the free troposphere pointing to modelled aerosol lifetimes that are too long. This is likely linked to too strong vertical transport and/or insufficient deposition efficiency during transport or export from the boundary layer, rather than chemical processing (in the case of sulphate aerosols). Underestimation of sulphate in the boundary layer implies potentially large errors in simulated aerosol–cloud interactions, via impacts on boundary-layer clouds.This evaluation has important implications for accurate assessment of air pollutants on regional air quality and global climate based on global model calculations. Ideally, models should be run at higher resolution over source regions to better simulate urban–rural pollutant gradients and/or chemical regimes, and also to better resolve pollutant processing and loss by wet deposition as well as vertical transport. Discrepancies in vertical distributions require further quantification and improvement since these are a key factor in the determination of radiative forcing from short-lived pollutants.

The volcanic fissure at Holuhraun, Iceland started at the end of August 2014 and continued for 6 months to the end of February 2015, with an extensive lava flow onto the Holuhraun plain. This event was associated with large SO2 emissions, amounting up to approximately 4.5 times the daily anthropogenic SO2 emitted from the 28 European Union countries, Norway, Switzerland and Iceland. In this paper we present results from EMEP/MSC-W model simulations to which we added 750 kg s−1 SO2 emissions at the Holuhraun plain from September to November (SON), testing three different emission heights. The three simulated SO2 concentrations, weighted with the OMI (Ozone Monitoring Instrument) satellite averaging kernel, are found to be within 30 % of the satellite-observed SO2 column burden. Constraining the SO2 column burden with the satellite data while using the kernel along with the three simulated height distributions of SO2, we estimate that the median of the daily burdens may have been between 13 and 40 kt in the North Atlantic area under investigation. We suggest this to be the uncertainty in the satellite-derived burdens of SO2, mainly due to the unknown vertical distribution of SO2. Surface observations in Europe outside Iceland showed concentration increases up to > 500 µg m−3 SO2 from volcanic plumes passing. Three well identified episodes, where the plume crossed several countries, are compared in detail to surface measurements. For all events, the general timing of the observed concentration peaks compared quite well to the model results. The overall changes to the European SO2 budget due to the volcanic fissure are estimated. Three-monthly wet deposition (SON) of SOx in the 28 European Union countries, Norway and Switzerland is found to be more than 30 % higher in the model simulation with Holuhraun emissions compared to a model simulation with no Holuhraun emissions. The largest increases, apart from extreme values on Iceland, are found on the coast of northern Norway, a region with frequent precipitation during westerly winds. Over a 3-month average (during SON 2014) over Europe, SO2 and PM2.5 surface concentrations, due to the volcanic emissions, increased by only ten and 6 % respectively. Although the percent increase of PM2.5 concentration is highest over Scandinavia and Scotland, an increase in PM exceedance days is found over Ireland and the already polluted Benelux region (up to 3 additional days), where any small increase in particulate matter concentration leads to an increase in exceedance days.

The spatial resolution of global climate models with interactive aerosol and the observations used to evaluate them is very different. Current models use grid spacings of ∼ 200 km, while satellite observations of aerosol use so-called pixels of ∼ 10 km. Ground site or airborne observations relate to even smaller spatial scales. We study the errors incurred due to different resolutions by aggregating high-resolution simulations (10 km grid spacing) over either the large areas of global model grid boxes ("perfect" model data) or small areas corresponding to the pixels of satellite measurements or the field of view of ground sites ("perfect" observations). Our analysis suggests that instantaneous root-mean-square (RMS) differences of perfect observations from perfect global models can easily amount to 30–160 %, for a range of observables like AOT (aerosol optical thickness), extinction, black carbon mass concentrations, PM2.5, number densities and CCN (cloud condensation nuclei). These differences, due entirely to different spatial sampling of models and observations, are often larger than measurement errors in real observations. Temporal averaging over a month of data reduces these differences more strongly for some observables (e.g. a threefold reduction for AOT), than for others (e.g. a twofold reduction for surface black carbon concentrations), but significant RMS differences remain (10–75 %). Note that this study ignores the issue of temporal sampling of real observations, which is likely to affect our present monthly error estimates. We examine several other strategies (e.g. spatial aggregation of observations, interpolation of model data) for reducing these differences and show their effectiveness. Finally, we examine consequences for the use of flight campaign data in global model evaluation and show that significant biases may be introduced depending on the flight strategy used.

In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 h using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distribution was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. Our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.

Aerosols have important impacts on air quality and climate, but the processes affecting their removal from the atmosphere are not fully understood and are poorly constrained by observations. This makes modelled aerosol lifetimes uncertain. In this study, we make use of an observational constraint on aerosol lifetimes provided by radionuclide measurements and investigate the causes of differences within a set of global models. During the Fukushima Dai-Ichi nuclear power plant accident of March 2011, the radioactive isotopes cesium-137 (137Cs) and xenon-133 (133Xe) were released in large quantities. Cesium attached to particles in the ambient air, approximately according to their available aerosol surface area. 137Cs size distribution measurements taken close to the power plant suggested that accumulation-mode (AM) sulfate aerosols were the main carriers of cesium. Hence, 137Cs can be used as a proxy tracer for the AM sulfate aerosol's fate in the atmosphere. In contrast, the noble gas 133Xe behaves almost like a passive transport tracer. Global surface measurements of the two radioactive isotopes taken over several months after the release allow the derivation of a lifetime of the carrier aerosol. We compare this to the lifetimes simulated by 19 different atmospheric transport models initialized with identical emissions of 137Cs that were assigned to an aerosol tracer with each model's default properties of AM sulfate, and 133Xe emissions that were assigned to a passive tracer. We investigate to what extent the modelled sulfate tracer can reproduce the measurements, especially with respect to the observed loss of aerosol mass with time. Modelled 137Cs and 133Xe concentrations sampled at the same location and times as station measurements allow a direct comparison between measured and modelled aerosol lifetime. The e-folding lifetime τe, calculated from station measurement data taken between 2 and 9 weeks after the start of the emissions, is 14.3 days (95 % confidence interval 13.1–15.7 days). The equivalent modelled τe lifetimes have a large spread, varying between 4.8 and 26.7 days with a model median of 9.4 ± 2.3 days, indicating too fast a removal in most models. Because sufficient measurement data were only available from about 2 weeks after the release, the estimated lifetimes apply to aerosols that have undergone long-range transport, i.e. not for freshly emitted aerosol. However, modelled instantaneous lifetimes show that the initial removal in the first 2 weeks was quicker (lifetimes between 1 and 5 days) due to the emissions occurring at low altitudes and co-location of the fresh plume with strong precipitation. Deviations between measured and modelled aerosol lifetimes are largest for the northernmost stations and at later time periods, suggesting that models do not transport enough of the aerosol towards the Arctic. The models underestimate passive tracer (133Xe) concentrations in the Arctic as well but to a smaller extent than for the aerosol (137Cs) tracer. This indicates that in addition to too fast an aerosol removal in the models, errors in simulated atmospheric transport towards the Arctic in most models also contribute to the underestimation of the Arctic aerosol concentrations.

Using the Community Climate System Model version 3 (CCSM3) including a dynamic global vegetation model, a set of 13 time slice experiments was carried out to study global climate variability between and within the Quaternary interglacials of Marine Isotope Stages (MISs) 1, 5, 11, 13, and 15. The selection of interglacial time slices was based on different aspects of inter- and intra-interglacial variability and associated astronomical forcing. The different effects of obliquity, precession, and greenhouse gas (GHG) forcing on global surface temperature and precipitation fields are illuminated. In most regions seasonal surface temperature anomalies can largely be explained by local insolation anomalies induced by the astronomical forcing. Climate feedbacks, however, may modify the surface temperature response in specific regions, most pronounced in the monsoon domains and the polar oceans. GHG forcing may also play an important role for seasonal temperature anomalies, especially at high latitudes and early Brunhes interglacials (MIS 13 and 15) when GHG concentrations were much lower than during the later interglacials. High- versus low-obliquity climates are generally characterized by strong warming over the Northern Hemisphere extratropics and slight cooling in the tropics during boreal summer. During boreal winter, a moderate cooling over large portions of the Northern Hemisphere continents and a strong warming at high southern latitudes is found. Beside the well-known role of precession, a significant role of obliquity in forcing the West African monsoon is identified. Other regional monsoon systems are less sensitive or not sensitive at all to obliquity variations during interglacials. Moreover, based on two specific time slices (394 and 615 ka), it is explicitly shown that the West African and Indian monsoon systems do not always vary in concert, challenging the concept of a global monsoon system on astronomical timescales. High obliquity can also explain relatively warm Northern Hemisphere high-latitude summer temperatures despite maximum precession around 495 ka (MIS 13). It is hypothesized that this obliquity-induced high-latitude warming may have prevented a glacial inception at that time.

The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ≈ 40, classification errors significantly increase.

The vertical profile of aerosol is important for its radiative effects, but weakly constrained by observations on the global scale, and highly variable among different models. To investigate the controlling factors in one particular model, we investigate the effects of individual processes in HadGEM3–UKCA and compare the resulting diversity of aerosol vertical profiles with the inter-model diversity from the AeroCom Phase II control experiment. In this way we show that (in this model at least) the vertical profile is controlled by a relatively small number of processes, although these vary among aerosol components and particle sizes. We also show that sufficiently coarse variations in these processes can produce a similar diversity to that among different models in terms of the global-mean profile and, to a lesser extent, the zonal-mean vertical position. However, there are features of certain models' profiles that cannot be reproduced, suggesting the influence of further structural differences between models. In HadGEM3–UKCA, convective transport is found to be very important in controlling the vertical profile of all aerosol components by mass. In-cloud scavenging is very important for all except mineral dust. Growth by condensation is important for sulfate and carbonaceous aerosol (along with aqueous oxidation for the former and ageing by soluble material for the latter). The vertical extent of biomass-burning emissions into the free troposphere is also important for the profile of carbonaceous aerosol. Boundary-layer mixing plays a dominant role for sea salt and mineral dust, which are emitted only from the surface. Dry deposition and below-cloud scavenging are important for the profile of mineral dust only. In this model, the microphysical processes of nucleation, condensation and coagulation dominate the vertical profile of the smallest particles by number (e.g. total CN > 3 nm), while the profiles of larger particles (e.g. CN > 100 nm) are controlled by the same processes as the component mass profiles, plus the size distribution of primary emissions. We also show that the processes that affect the AOD-normalised radiative forcing in the model are predominantly those that affect the vertical mass distribution, in particular convective transport, in-cloud scavenging, aqueous oxidation, ageing and the vertical extent of biomass-burning emissions.

BACKGROUND:Excessive workload may impair patient safety. However, little is known about emergency care providers' workload during the treatment of life-threatening cases including cardiopulmonary resuscitation (CPR). Therefore, we tested the hypothesis that subjective and physiological indicators of workload are associated with the patient's initial NACA score and that workload is particularly high during CPR. METHODS:NASA task load index (NASA-tlx) and alarm codes were obtained for 216 sorties of pre-hospital emergency medical care. Furthermore, initial NACA scores of 140 patients were extracted from the physicians' protocols. The physiological workload indicators mean heart rate (HR) and permutation entropy (PeEn) were calculated for 51 sorties of primary care. General linear mixed models were used to analyze the association of NACA scores with subjective (NASA-tlx) and physiological (mean HR, PeEn) measures of workload. RESULTS:In contrast to the physiological variables PeEn (p = 0.10) and HR (p = 0.19), the mental (p

The full set of electromechanical data of langasite (La3Ga5SiO14) is determined in the temperature range from 20 to 900 °C using differently oriented bulk acoustic wave resonators. For data evaluation a physical model of vibration is developed and applied. Thereby, special emphasis is taken on mechanical and electrical losses at high temperatures. The resulting data set is used to calculate the properties of surface acoustic waves. Direct comparison with experimental data such as velocity, coupling coefficients and propagation loss measured using surface acoustic wave devices with two different crystal orientations shows good agreement.

The European MACC (Monitoring Atmospheric Composition and Climate) project is preparing the operational Copernicus Atmosphere Monitoring Service (CAMS), one of the services of the European Copernicus Programme on Earth observation and environmental services. MACC uses data assimilation to combine in situ and remote sensing observations with global and regional models of atmospheric reactive gases, aerosols, and greenhouse gases, and is based on the Integrated Forecasting System of the European Centre for Medium-Range Weather Forecasts (ECMWF). The global component of the MACC service has a dedicated validation activity to document the quality of the atmospheric composition products. In this paper we discuss the approach to validation that has been developed over the past 3 years. Topics discussed are the validation requirements, the operational aspects, the measurement data sets used, the structure of the validation reports, the models and assimilation systems validated, the procedure to introduce new upgrades, and the scoring methods. One specific target of the MACC system concerns forecasting special events with high-pollution concentrations. Such events receive extra attention in the validation process. Finally, a summary is provided of the results from the validation of the latest set of daily global analysis and forecast products from the MACC system reported in November 2014.

This paper presents a summary of the work done within the European Union's Seventh Framework Programme project ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants). ECLIPSE had a unique systematic concept for designing a realistic and effective mitigation scenario for short-lived climate pollutants (SLCPs; methane, aerosols and ozone, and their precursor species) and quantifying its climate and air quality impacts, and this paper presents the results in the context of this overarching strategy. The first step in ECLIPSE was to create a new emission inventory based on current legislation (CLE) for the recent past and until 2050. Substantial progress compared to previous work was made by including previously unaccounted types of sources such as flaring of gas associated with oil production, and wick lamps. These emission data were used for present-day reference simulations with four advanced Earth system models (ESMs) and six chemistry transport models (CTMs). The model simulations were compared with a variety of ground-based and satellite observational data sets from Asia, Europe and the Arctic. It was found that the models still underestimate the measured seasonality of aerosols in the Arctic but to a lesser extent than in previous studies. Problems likely related to the emissions were identified for northern Russia and India, in particular. To estimate the climate impacts of SLCPs, ECLIPSE followed two paths of research: the first path calculated radiative forcing (RF) values for a large matrix of SLCP species emissions, for different seasons and regions independently. Based on these RF calculations, the Global Temperature change Potential metric for a time horizon of 20 years (GTP20) was calculated for each SLCP emission type. This climate metric was then used in an integrated assessment model to identify all emission mitigation measures with a beneficial air quality and short-term (20-year) climate impact. These measures together defined a SLCP mitigation (MIT) scenario. Compared to CLE, the MIT scenario would reduce global methane (CH4) and black carbon (BC) emissions by about 50 and 80 %, respectively. For CH4, measures on shale gas production, waste management and coal mines were most important. For non-CH4 SLCPs, elimination of high-emitting vehicles and wick lamps, as well as reducing emissions from gas flaring, coal and biomass stoves, agricultural waste, solvents and diesel engines were most important. These measures lead to large reductions in calculated surface concentrations of ozone and particulate matter. We estimate that in the EU, the loss of statistical life expectancy due to air pollution was 7.5 months in 2010, which will be reduced to 5.2 months by 2030 in the CLE scenario. The MIT scenario would reduce this value by another 0.9 to 4.3 months. Substantially larger reductions due to the mitigation are found for China (1.8 months) and India (11–12 months). The climate metrics cannot fully quantify the climate response. Therefore, a second research path was taken. Transient climate ensemble simulations with the four ESMs were run for the CLE and MIT scenarios, to determine the climate impacts of the mitigation. In these simulations, the CLE scenario resulted in a surface temperature increase of 0.70 ± 0.14 K between the years 2006 and 2050. For the decade 2041–2050, the warming was reduced by 0.22 ± 0.07 K in the MIT scenario, and this result was in almost exact agreement with the response calculated based on the emission metrics (reduced warming of 0.22 ± 0.09 K). The metrics calculations suggest that non-CH4 SLCPs contribute ~ 22 % to this response and CH4 78 %. This could not be fully confirmed by the transient simulations, which attributed about 90 % of the temperature response to CH4 reductions. Attribution of the observed temperature response to non-CH4 SLCP emission reductions and BC specifically is hampered in the transient simulations by small forcing and co-emitted species of the emission basket chosen. Nevertheless, an important conclusion is that our mitigation basket as a whole would lead to clear benefits for both air quality and climate. The climate response from BC reductions in our study is smaller than reported previously, possibly because our study is one of the first to use fully coupled climate models, where unforced variability and sea ice responses cause relatively strong temperature fluctuations that may counteract (and, thus, mask) the impacts of small emission reductions. The temperature responses to the mitigation were generally stronger over the continents than over the oceans, and with a warming reduction of 0.44 K (0.39–0.49) K the largest over the Arctic. Our calculations suggest particularly beneficial climate responses in southern Europe, where surface warming was reduced by about 0.3 K and precipitation rates were increased by about 15 (6–21) mm yr−1 (more than 4 % of total precipitation) from spring to autumn. Thus, the mitigation could help to alleviate expected future drought and water shortages in the Mediterranean area. We also report other important results of the ECLIPSE project.

The concentrations of sulfate, black carbon (BC) and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality and especially the high concentrations associated with Arctic Haze. In this study, we evaluate sulfate and BC concentrations from eleven different models driven with the same emission inventory against a comprehensive pan-Arctic measurement data set over a time period of 2 years (2008–2009). The set of models consisted of one Lagrangian particle dispersion model, four chemistry transport models (CTMs), one atmospheric chemistry-weather forecast model and five chemistry climate models (CCMs), of which two were nudged to meteorological analyses and three were running freely. The measurement data set consisted of surface measurements of equivalent BC (eBC) from five stations (Alert, Barrow, Pallas, Tiksi and Zeppelin), elemental carbon (EC) from Station Nord and Alert and aircraft measurements of refractory BC (rBC) from six different campaigns. We find that the models generally captured the measured eBC or rBC and sulfate concentrations quite well, compared to previous comparisons. However, the aerosol seasonality at the surface is still too weak in most models. Concentrations of eBC and sulfate averaged over three surface sites are underestimated in winter/spring in all but one model (model means for January–March underestimated by 59 and 37 % for BC and sulfate, respectively), whereas concentrations in summer are overestimated in the model mean (by 88 and 44 % for July–September), but with overestimates as well as underestimates present in individual models. The most pronounced eBC underestimates, not included in the above multi-site average, are found for the station Tiksi in Siberia where the measured annual mean eBC concentration is 3 times higher than the average annual mean for all other stations. This suggests an underestimate of BC sources in Russia in the emission inventory used. Based on the campaign data, biomass burning was identified as another cause of the modeling problems. For sulfate, very large differences were found in the model ensemble, with an apparent anti-correlation between modeled surface concentrations and total atmospheric columns. There is a strong correlation between observed sulfate and eBC concentrations with consistent sulfate/eBC slopes found for all Arctic stations, indicating that the sources contributing to sulfate and BC are similar throughout the Arctic and that the aerosols are internally mixed and undergo similar removal. However, only three models reproduced this finding, whereas sulfate and BC are weakly correlated in the other models. Overall, no class of models (e.g., CTMs, CCMs) performed better than the others and differences are independent of model resolution.

In the present work, atmospheric mineral dust from a MACC-II short reanalysis run for 2 years (2007–2008) has been evaluated over northern Africa and the Middle East using satellite aerosol products (from MISR, MODIS and OMI satellite sensors), ground-based AERONET data, in situ PM10 concentrations from AMMA, and extinction vertical profiles from two ground-based lidars and CALIOP satellite-based lidar. The MACC-II aerosol optical depth (AOD) spatial and temporal (seasonal and interannual) variability shows good agreement with those provided by satellite sensors. The capability of the model to reproduce the AOD, Ångström exponent (AE) and dust optical depth (DOD) from daily to seasonal time-scale is quantified over 26 AERONET stations located in eight geographically distinct regions by using statistical parameters. Overall DOD seasonal variation is fairly well simulated by MACC-II in all regions, although the correlation is significantly higher in dust transport regions than in dust source regions. The ability of MACC-II in reproducing dust vertical profiles has been assessed by comparing seasonal averaged extinction vertical profiles simulated by MACC-II under dust conditions with corresponding extinction profiles obtained with lidar instruments at M'Bour and Santa Cruz de Tenerife, and with CALIOP. We find a good agreement in dust layers structures and averaged extinction vertical profiles between MACC-II, the lidars and CALIOP above the marine boundary layer from 1 to 6 km. Surface dust daily mean concentrations from MACC-II reanalysis has been evaluated with daily averaged PM10 at three monitoring stations of the Sahelian Dust Transect. MACC-II correctly reproduces daily to interannual surface dust concentration variability, although it underestimates daily and monthly means all year long, especially in winter and early spring (dry season). MACC-II reproduces well the dust variability recorded along the station transect which reflects the variability in dust emission by different Saharan sources, but fails in reproducing the sporadic and very strong dust events associated to mesoscale convective systems during the wet season.

The present study analyses the sign, strength, and working mechanism of the vegetation–precipitation feedback over North Africa in middle (6 ka BP) and early Holocene (9 ka BP) simulations using the comprehensive coupled climate–vegetation model CCSM3-DGVM (Community Climate System Model version 3 and a dynamic global vegetation model). The coupled model simulates enhanced summer rainfall and a northward migration of the West African monsoon trough along with an expansion of the vegetation cover for the early and middle Holocene compared to the pre-industrial period. It is shown that dynamic vegetation enhances the orbitally triggered summer precipitation anomaly by approximately 20% in the Sahara–Sahel region (10–25° N, 20° W–30° E) in both the early and mid-Holocene experiments compared to their fixed-vegetation counterparts. The primary vegetation–rainfall feedback identified here operates through surface latent heat flux anomalies by canopy evaporation and transpiration and their effect on the mid-tropospheric African easterly jet, whereas the effects of vegetation changes on surface albedo and local water recycling play a negligible role. Even though CCSM3-DGVM simulates a positive vegetation–precipitation feedback in the North African region, this feedback is not strong enough to produce multiple equilibrium climate-ecosystem states on a regional scale.

BACKGROUND:It has been shown that linear and non-linear heart rate variability (HRV) metrics are suitable to assess workload of anesthetists administering anesthesia. In pre-hospital emergency care, these parameters have not yet been evaluated. We hypothesized that heart rate (HR) and HRV metrics discriminate between differing workload levels of an emergency physician. METHODS:Electrocardiograms were obtained from 13 emergency physicians. Mean HR, ten linear and seven non-linear HRV metrics were analyzed. For each sortie, four different levels of workload were defined. Mixed-effects models and the area under the receiver operating characteristics curve (AUC) were used to test and quantify the HR and HRV metrics' ability to discriminate between levels of workload. This was conducted for mean HR and each HRV metric as well as for groups of metrics (time domain vs. frequency domain vs. non-linear metrics). RESULTS:The non-linear HRV metric Permutation entropy (PeEn) discriminated best between the time before the alarm and primary patient care (AUC = 0.998, 1st rank of 18 HRV metrics). In contrast, AUC of the mean HR was low (0.558, 17th rank). In the multivariable approach, the non-linear HRV metrics provided a higher AUC (0.998) compared to the frequency domain (0.677) and to the time domain metrics (0.680). CONCLUSION:Non-linear heart rate metrics and, specifically, PeEn provided good validity for the assessment of different levels of a physician's workload in the setting of pre-hospital emergency care. In contradiction to earlier findings, the physicians' mean HR was not a valid marker of workload.

A new method is presented for the determination of cloud top heights using the footage of a time-lapse camera that is placed above a frequently occurring cloud layer in a mountain valley. Contact points between cloud tops and underlying terrain are automatically detected in the camera image based on differences in the brightness, texture and movement of cloudy and non-cloudy areas. The height of the detected cloud top positions is determined by comparison with a digital elevation model projected to the view of the camera. The technique has been validated using data about the cloud immersion of a second camera as well as via visual assessment. The validation shows a high detection quality, especially regarding the requirements for the validation of satellite cloud top retrieval algorithms.

Atmospheric black carbon (BC) absorbs solar radiation, and exacerbates global warming through exerting positive radiative forcing (RF). However, the contribution of BC to ongoing changes in global climate is under debate. Anthropogenic BC emissions, and the resulting distribution of BC concentration, are highly uncertain. In particular, long-range transport and processes affecting BC atmospheric lifetime are poorly understood. Here we discuss whether recent assessments may have overestimated present-day BC radiative forcing in remote regions. We compare vertical profiles of BC concentration from four recent aircraft measurement campaigns to simulations by 13 aerosol models participating in the AeroCom Phase II intercomparison. An atmospheric lifetime of BC of less than 5 days is shown to be essential for reproducing observations in remote ocean regions, in line with other recent studies. Adjusting model results to measurements in remote regions, and at high altitudes, leads to a 25% reduction in AeroCom Phase II median direct BC forcing, from fossil fuel and biofuel burning, over the industrial era. The sensitivity of modelled forcing to BC vertical profile and lifetime highlights an urgent need for further flight campaigns, close to sources and in remote regions, to provide improved quantification of BC effects for use in climate policy.

This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

The ammonia cycle and nitrate particle formation are introduced into the LMDz-INCA (Laboratoire de Météorologie Dynamique, version 4 – INteraction with Chemistry and Aerosols, version 3) global model. An important aspect of this new model is that both fine nitrate particle formation in the accumulation mode and coarse nitrate forming on existing dust and sea-salt particles are considered. The model simulates distributions of nitrates and related species in agreement with previous studies and observations. The calculated present-day total nitrate direct radiative forcing since the pre-industrial is −0.056 W m−2. This forcing corresponds to 18% of the sulfate forcing. Fine particles largely dominate the nitrate forcing, representing close to 90% of this value. The model has been used to investigate the future changes in nitrates and direct radiative forcing of climate based on snapshot simulations for the four representative concentration pathway (RCP) scenarios and for the 2030, 2050, and 2100 time horizons. Due to a decrease in fossil fuel emissions in the future, the concentration of most of the species involved in the nitrate–ammonium–sulfate system drop by 2100 except for ammonia, which originates from agricultural practices and for which emissions significantly increase in the future. Despite the decrease of nitrate surface levels in Europe and North America, the global burden of accumulation mode nitrates increases by up to a factor of 2.6 in 2100. This increase in ammonium nitrate in the future arises despite decreasing NOx emissions due to increased availability of ammonia to form ammonium nitrate. The total aerosol direct forcing decreases from its present-day value of −0.234 W m−2 to a range of −0.070 to −0.130 W m−2 in 2100 based on the considered scenario. The direct forcing decreases for all aerosols except for nitrates, for which the direct negative forcing increases to a range of −0.060 to −0.115 W m−2 in 2100. Including nitrates in the radiative forcing calculations increases the total direct forcing of aerosols by a factor of 1.3 in 2000, by a factor of 1.7–2.6 in 2030, by 1.9–4.8 in 2050, and by 6.4–8.6 in 2100. These results show that the agricultural emissions of ammonia will play a key role in the future mitigation of climate change, with nitrates becoming the dominant contributor to the anthropogenic aerosol optical depth during the second half of the 21st century and significantly increasing the calculated aerosol direct forcing. This significant increase in the influence that nitrate exerts on climate in the future will at the same time affect regional air quality and nitrogen deposition to the ecosystem.

Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.

Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are −4.4 (−13.2 to +10.7) ng g−1 for an earlier phase of AeroCom models (phase I), and +4.1 (−13.0 to +21.4) ng g−1 for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng g−1. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model–measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60–90° N) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07–0.25) W m−2 and 0.18 (0.06–0.28) W m−2 in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W m−2 for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.

The quantification and understanding of direct aerosol forcing is essential in the study of climate. One of the main issues that makes its quantification difficult is the lack of a complete understanding of the role of the vertical distribution of aerosols and clouds. This work aims at reducing the uncertainty of aerosol top-of-the-atmosphere (TOA) forcing due to the vertical superposition of several short-lived atmospheric components, in particular different aerosol species and clouds. We propose a method to quantify the contribution of different parts of the atmospheric column to the TOA forcing as well as to evaluate the contribution to model differences that is exclusively due to different spatial distributions of aerosols and clouds. We investigate the contribution of aerosol above, below and in clouds by using added diagnostics in the aerosol–climate model LMDz. We also compute the difference between the TOA forcing of the ensemble of the aerosols and the sum of the forcings from individual species in clear sky. This difference is found to be moderate for the global average (14%) but can reach high values regionally (up to 100%). Nonlinear effects are even more important when superposing aerosols and clouds. Four forcing computations are performed: one where the full aerosol 3-D distribution is used, and then three where aerosols are confined to regions above, inside and below clouds, respectively. We find that the TOA forcing of aerosols depends crucially on the presence of clouds and on their position relative to that of the aerosol, in particular for black carbon (BC). We observe a strong enhancement of the TOA forcing of BC above clouds, attenuation for BC below clouds, and a moderate enhancement when BC is found within clouds. BC above clouds accounts for only about 30% of the total BC optical depth but for 55% of the forcing, while forcing efficiency increases by a factor of 7.5 when passing from below to above clouds. The different behaviour of forcing nonlinearities for these three components of the atmospheric column encouraged us to develop the method for application to inter-model variability studies by reading 3-D aerosol and cloud fields from different general circulation models (GCMs) into the same model. We apply the method to the comparison of forcing due to the aerosols and clouds distributions of the general circulation models LMDz and SPRINTARS. The different amount of BC above but also within clouds is revealed to play a major role on the differences of cloudy-sky forcings between the two models, which can exceed 100% regionally.