Effects of reduced and business-as-usual CO2 emission scenarios on the algal territories of the damselfish Pomacentrus wardi (Pomacentridae)

Turf algae are a very important component of coral reefs, featuring high growth and turnover rates, whilst covering large areas of substrate. As food for many organisms, turf algae have an important role in the ecosystem. Farming damselfish can modify the species composition and productivity of such algal assemblages, while defending them against intruders. Like all organisms however, turf algae and damselfishes have the potential to be affected by future changes in seawater (SW) temperature and pCO2. In this study, algal assemblages, in the presence and absence of farming Pomacentrus wardi were exposed to two combinations of SW temperature and pCO2 levels projected for the austral spring of 2100 (the B1 "reduced" and the A1FI "business-as-usual" CO2 emission scenarios) at Heron Island (GBR, Australia). These assemblages were dominated by the presence of red algae and non-epiphytic cyanobacteria, i.e. cyanobacteria that grow attached to the substrate rather than on filamentous algae. The endpoint algal composition was mostly controlled by the presence/absence of farming damselfish, despite a large variability found between the algal assemblages of individual fish. Different scenarios appeared to be responsible for a mild, species specific change in community composition, observable in some brown and green algae, but only in the absence of farming fish. Farming fish appeared unaffected by the conditions to which they were exposed. Algal biomass reductions were found under "reduced" CO2 emission, but not "business-as-usual" scenarios. This suggests that action taken to limit CO2 emissions may, if the majority of algae behave similarly across all seasons, reduce the potential for phase shifts that lead to algal dominated communities. At the same time the availability of food resources to damselfish and other herbivores would be smaller under "reduced" emission scenarios.

Comparison and Assessment of Two Emission inventories for the Madrid Region

Emission inventories are databases that aim to describe the polluting activities that occur across a certain geographic domain. According to the spatial scale, the availability of information will vary as well as the applied assumptions, which will strongly influence its quality, accuracy and representativeness. This study compared and contrasted two emission inventories describing the Greater Madrid Region (GMR) under an air quality simulation approach. The chosen inventories were the National Emissions Inventory (NEI) and the Regional Emissions Inventory of the Greater Madrid Region (REI). Both of them were used to feed air quality simulations with the CMAQ modelling system, and the results were compared with observations from the air quality monitoring network in the modelled domain. Through the application of statistical tools, the analysis of emissions at cell level and cell – expansion procedures, it was observed that the National Inventory showed better results for describing on – road traffic activities and agriculture, SNAP07 and SNAP10. The accurate description of activities, the good characterization of the vehicle fleet and the correct use of traffic emission factors were the main causes of such a good correlation. On the other hand, the Regional Inventory showed better descriptions for non – industrial combustion (SNAP02) and industrial activities (SNAP03). It incorporated realistic emission factors, a reasonable fuel mix and it drew upon local information sources to describe these activities, while NEI relied on surrogation and national datasets which leaded to a poorer representation. Off – road transportation (SNAP08) was similarly described by both inventories, while the rest of the SNAP activities showed a marginal contribution to the overall emissions.

Comparasion of road traffic emission models in Madrid (Spain)

Many cities in Europe have difficulties to meet the air quality standards set by the European legislation, most particularly the annual mean Limit Value for NO2. Road transport is often the main source of air pollution in urban areas and therefore, there is an increasing need to estimate current and future traffic emissions as accurately as possible. As a consequence, a number of specific emission models and emission factors databases have been developed recently. They present important methodological differences and may result in largely diverging emission figures and thus may lead to alternative policy recommendations. This study compares two approaches to estimate road traffic emissions in Madrid (Spain): the COmputer Programme to calculate Emissions from Road Transport (COPERT4 v.8.1) and the Handbook Emission Factors for Road Transport (HBEFA v.3.1), representative of the ‘average-speed’ and ‘traffic situation’ model types respectively. The input information (e.g. fleet composition, vehicle kilometres travelled, traffic intensity, road type, etc.) was provided by the traffic model developed by the Madrid City Council along with observations from field campaigns. Hourly emissions were computed for nearly 15 000 road segments distributed in 9 management areas covering the Madrid city and surroundings. Total annual NOX emissions predicted by HBEFA were a 21% higher than those of COPERT. The discrepancies for NO2 were lower (13%) since resulting average NO2/NOX ratios are lower for HBEFA. The larger differences are related to diesel vehicle emissions under “stop & go” traffic conditions, very common in distributor/secondary roads of the Madrid metropolitan area. In order to understand the representativeness of these results, the resulting emissions were integrated in an urban scale inventory used to drive mesoscale air quality simulations with the Community Multiscale Air Quality (CMAQ) modelling system (1 km2 resolution). Modelled NO2 concentrations were compared with observations through a series of statistics. Although there are no remarkable differences between both model runs, the results suggest that HBEFA may overestimate traffic emissions. However, the results are strongly influenced by methodological issues and limitations of the traffic model. This study was useful to provide a first alternative estimate to the official emission inventory in Madrid and to identify the main features of the traffic model that should be improved to support the application of an emission system based on “real world” emission factors.

Emission inventories and modeling requirements for the development of air quality plans. Application to Madrid (Spain)

Modeling is an essential tool for the development of atmospheric emission abatement measures and air quality plans. Most often these plans are related to urban environments with high emission density and population exposure. However, air quality modeling in urban areas is a rather challenging task. As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large urban areas across Europe, particularly for NO2. This also implies that emission inventories must satisfy a number of conditions such as consistency across the spatial scales involved in the analysis, consistency with the emission inventories used for regulatory purposes and versatility to match the requirements of different air quality and emission projection models. This study reports the modeling activities carried out in Madrid (Spain) highlighting the atmospheric emission inventory development and preparation as an illustrative example of the combination of models and data needed to develop a consistent air quality plan at urban level. These included a series of source apportionment studies to define contributions from the international, national, regional and local sources in order to understand to what extent local authorities can enforce meaningful abatement measures. Moreover, source apportionment studies were conducted in order to define contributions from different sectors and to understand the maximum feasible air quality improvement that can be achieved by reducing emissions from those sectors, thus targeting emission reduction policies to the most relevant activities. Finally, an emission scenario reflecting the effect of such policies was developed and the associated air quality was modeled.

Toward a climate-dependent paradigm of ammonia emission & deposition.

Existing descriptions of bi-directional ammonia (NH3) land–atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission–deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28–67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45–85) Tg N in 2008 to reach 132 (89–179) Tg by 2100.

Development and assessment of traffic-related emission abatement measures for the Madrid city (Spain) through the WRF-SMOKE-CMAQ modelling system

The achievement of the limit values established in the European legislation pose an important handicap for large urban areas with intense road traffic, such as Madrid (Spain). Despite permanent measures included in air quality plans it is important to assess additional measures that may be temporally applied under unfavourable conditions. This paper reports on the simulation of different traffic restriction strategies in Madrid for high-pollution episodes.

Modulation of cognition-specific cortical activity by gonadal steroids: A positron-emission tomography study in women

There is considerable evidence from animal studies that gonadal steroid hormones modulate neuronal activity and affect behavior. To study this in humans directly, we used H215O positron-emission tomography to measure regional cerebral blood flow (rCBF) in young women during three pharmacologically controlled hormonal conditions spanning 4–5 months: ovarian suppression induced by the gonadotropin-releasing hormone agonist leuprolide acetate (Lupron), Lupron plus estradiol replacement, and Lupron plus progesterone replacement. Estradiol and progesterone were administered in a double-blind cross-over design. On each occasion positron-emission tomography scans were performed during (i) the Wisconsin Card Sorting Test, a neuropsychological test that physiologically activates prefrontal cortex (PFC) and an associated cortical network including inferior parietal lobule and posterior inferolateral temporal gyrus, and (ii) a no-delay matching-to-sample sensorimotor control task. During treatment with Lupron alone (i.e., with virtual absence of gonadal steroid hormones), there was marked attenuation of the typical Wisconsin Card Sorting Test activation pattern even though task performance did not change. Most strikingly, there was no rCBF increase in PFC. When either progesterone or estrogen was added to the Lupron regimen, there was normalization of the rCBF activation pattern with augmentation of the parietal and temporal foci and return of the dorsolateral PFC activation. These data directly demonstrate that the hormonal milieu modulates cognition-related neural activity in humans.

Muscle protein synthesis by positron-emission tomography with l-[methyl-11C]methionine in adult humans

Existing methods for assessing protein synthetic rates (PSRs) in human skeletal muscle are invasive and do not readily provide information about individual muscle groups. Recent studies in canine skeletal muscle yielded PSRs similar to results of simultaneous stable isotope measurements using l-[1-13C, methyl-2H3]methionine, suggesting that positron-emission tomography (PET) with l-[methyl-11C]methionine could be used along with blood sampling and a kinetic model to provide a less invasive, regional assessment of PSR. We have extended and refined this method in an investigation with healthy volunteers studied in the postabsorptive state. They received ≈25 mCi of l-[methyl-11C]methionine with serial PET imaging of the thighs and arterial blood sampling for a period of 90 min. Tissue and metabolite-corrected arterial blood time activity curves were fitted to a three-compartment model. PSR (nmol methionine⋅min−1⋅g muscle tissue−1) was calculated from the fitted parameter values and the plasma methionine concentrations, assuming equal rates of protein synthesis and degradation. Pooled mean PSR for the anterior and posterior sites was 0.50 ± 0.040. When converted to a fractional synthesis rate for mixed proteins in muscle, assuming a protein-bound methionine content of muscle tissue, the value of 0.125 ± 0.01%⋅h−1 compares well with estimates from direct tracer incorporation studies, which generally range from ≈0.05 to 0.09%⋅h−1. We conclude that PET can be used to estimate skeletal muscle PSR in healthy human subjects and that it holds promise for future in vivo, noninvasive studies of the influences of physiological factors, pharmacological manipulations, and disease states on this important component of muscle protein turnover and balance.

Positron-emission tomography imaging of long-term shape recognition challenges

Long-term visual memory performance was impaired by two types of challenges: a diazepam challenge on acquisition and a sensory challenge on recognition. Using positron-emission tomography regional cerebral blood flow imaging, we studied the effect of these challenges on regional brain activation during the delayed recognition of abstract visual shapes as compared with a baseline fixation task. Both challenges induced a significant decrease in differential activation in the left fusiform gyrus, suggesting that this region is involved in the automatic or volitional comparison of incoming and stored stimuli. In contrast, thalamic differential activation increased in response to memory challenges. This increase might reflect enhanced retrieval attempts as a compensatory mechanism for restoring recognition performance.

Correlation of regional cerebral blood flow and change of plasma sodium concentration during genesis and satiation of thirst

Positron emission tomography studies were conducted during genesis of moderate thirst by rapid i.v. infusion of hypertonic saline (0.51 M) and after satiation of thirst by drinking water. The correlation of regional cerebral blood flow with the change in the plasma Na concentration showed a significant group of cerebral activations in the anterior cingulate region and also a site in the middle temporal gyrus and in the periaqueductal gray. Strongest deactivations occurred in the parahippocampal and frontal gyri. The data are consistent with an important role of the anterior cingulate in the genesis of thirst.

Memory for object features versus memory for object location: a positron-emission tomography study of encoding and retrieval processes.

Regional cerebral blood flow was measured with positron-emission tomography during two encoding and two retrieval tasks that were designed to compare memory for object features with memory for object locations. Bilateral increases in regional cerebral blood flow were observed in both anterior and posterior regions of inferior temporal cortex and in ventral regions of prestriate cortex, when the condition that required retrieval of object locations was subtracted from the condition that required retrieval of object features. During encoding, these changes were less pronounced and were restricted to the left inferior temporal cortex and right ventral prestriate cortex. In contrast, both encoding and retrieval of object location were associated with bilateral changes in dorsal prestriate and posterior parietal cortex. Finally, the two encoding conditions activated left frontal lobe regions preferentially, whereas the two retrieval conditions activated right frontal lobe regions. These findings confirm that, in human subjects, memory for object features is mediated by a distributed system that includes ventral prestriate cortex and both anterior and posterior regions of the inferior temporal gyrus. In contrast, memory for the locations of objects appears to be mediated by an anatomically distinct system that includes more dorsal regions of prestriate cortex and posterior regions of the parietal lobe.

Positron-emission tomography studies of cross-modality inhibition in selective attentional tasks: closing the "mind's eye".

It is a familiar experience that we tend to close our eyes or divert our gaze when concentrating attention on cognitively demanding tasks. We report on the brain activity correlates of directing attention away from potentially competing visual processing and toward processing in another sensory modality. Results are reported from a series of positron-emission tomography studies of the human brain engaged in somatosensory tasks, in both "eyes open" and "eyes closed" conditions. During these tasks, there was a significant decrease in the regional cerebral blood flow in the visual cortex, which occurred irrespective of whether subjects had to close their eyes or were instructed to keep their eyes open. These task-related deactivations of the association areas belonging to the nonrelevant sensory modality were interpreted as being due to decreased metabolic activity. Previous research has clearly demonstrated selective activation of cortical regions involved in attention-demanding modality-specific tasks; however, the other side of this story appears to be one of selective deactivation of unattended areas.

Neural-network-based classification of cognitively normal, demented, Alzheimer disease and vascular dementia from single photon emission with computed tomography image data from brain.

Single photon emission with computed tomography (SPECT) hexamethylphenylethyleneamineoxime technetium-99 images were analyzed by an optimal interpolative neural network (OINN) algorithm to determine whether the network could discriminate among clinically diagnosed groups of elderly normal, Alzheimer disease (AD), and vascular dementia (VD) subjects. After initial image preprocessing and registration, image features were obtained that were representative of the mean regional tissue uptake. These features were extracted from a given image by averaging the intensities over various regions defined by suitable masks. After training, the network classified independent trials of patients whose clinical diagnoses conformed to published criteria for probable AD or probable/possible VD. For the SPECT data used in the current tests, the OINN agreement was 80 and 86% for probable AD and probable/possible VD, respectively. These results suggest that artificial neural network methods offer potential in diagnoses from brain images and possibly in other areas of scientific research where complex patterns of data may have scientifically meaningful groupings that are not easily identifiable by the researcher.

Transferability of Regional Permafrost Disturbance Susceptibility Modelling Using Generalized Linear and Generalized Additive Models

To effectively assess and mitigate risk of permafrost disturbance, disturbance-p rone areas can be predicted through the application of susceptibility models. In this study we developed regional susceptibility models for permafrost disturbances using a field disturbance inventory to test the transferability of the model to a broader region in the Canadian High Arctic. Resulting maps of susceptibility were then used to explore the effect of terrain variables on the occurrence of disturbances within this region. To account for a large range of landscape charac- teristics, the model was calibrated using two locations: Sabine Peninsula, Melville Island, NU, and Fosheim Pen- insula, Ellesmere Island, NU. Spatial patterns of disturbance were predicted with a generalized linear model (GLM) and generalized additive model (GAM), each calibrated using disturbed and randomized undisturbed lo- cations from both locations and GIS-derived terrain predictor variables including slope, potential incoming solar radiation, wetness index, topographic position index, elevation, and distance to water. Each model was validated for the Sabine and Fosheim Peninsulas using independent data sets while the transferability of the model to an independent site was assessed at Cape Bounty, Melville Island, NU. The regional GLM and GAM validated well for both calibration sites (Sabine and Fosheim) with the area under the receiver operating curves (AUROC) N 0.79. Both models were applied directly to Cape Bounty without calibration and validated equally with AUROC's of 0.76; however, each model predicted disturbed and undisturbed samples differently. Addition- ally, the sensitivity of the transferred model was assessed using data sets with different sample sizes. Results in- dicated that models based on larger sample sizes transferred more consistently and captured the variability within the terrain attributes in the respective study areas. Terrain attributes associated with the initiation of dis- turbances were similar regardless of the location. Disturbances commonly occurred on slopes between 4 and 15°, below Holocene marine limit, and in areas with low potential incoming solar radiation

Russian gas industry - current condition and prospects; New regional 'in-security' system in Central Asia; Caspian oil and gas: the facts at the end of the year 2000. OSW Study 1/2001

Russian gas industry: The current condition of the gas industry is one of the most crucial factors influencing the Russian state·s functioning, internal situation and international position. Not only is gas the principal energy resource in Russia, it also subsidises other sectors of the economy. Status of the main European gas exporter strengthens also Russia's importance in the international arena. New regional in-security: Ten years have passed since the Central Asian states declared their independence, but their relationship with Russia still remains close, and the latter treats them as its exclusive zone of influence. A crucial reason for keeping Central Asia within the orbit of Moscow·s influence is the fact that Russia exercises control over the most important transport routes out of the region of raw materials for the power industry, on which the economic development of Asia depends on. But this is the only manifestation of Central Asia·s economic dependence on Russia. Moscow lacks solid economic instruments (i.e. investment input or power industry dependence) to shape the situation in the region. Caspian oil and gas: Caspian stocks of energy resources are not, and most probably will not be, of any great significance on the world scale. Nevertheless it is the Caspian region which will have the opportunity to become an oil exporter which will reduce the dependence of the European countries on Arabian oil, and which will guarantee Russia the quantities of gas which are indispensable both for meeting its internal demands and for maintaining its current level of export. For Azerbaijan, Kazakhstan and Turkmenistan, the confirmation of the existence of successive oil strata is not only an opportunity to increase income, but also an additional bargaining chip in the game for the future of the whole region. The stake in this game is the opportunity to limit the economic, and by extension the political influences of Russia in the region.