Heat flow in the Black and Mediterranean seas

Results of heat-flow measurements in the western Black Sea and within the African-Sicilian region of the Mediterranean Sea are presented. New data reveal a well-defined correlation with the deep-seated geologic structure of the regions examined. A heat-flow anomaly within the Pantelleria graben, in the authors' opinion, is a consequence of connective heat transfer along channels of disjunctive faults.

Heat flow measurements in sediments of the Norwegian Sea (Table 1)

During cruises in the Norwegian Sea in 1969 and 1972 seven heat flow values were measured between Iceland and the Voring Plateau. The six eastern values of this profile show a positive trend east-southeastwards which coincides with a possible transition from oceanic to continental crust suggested by seismic results. One heat flow value taken near Iceland and 250 miles west of the others reflects the influence of the Mid-Atlantic Ridge. An estimation of the heat flow at a depth of 15 km below the measuring localities yields values with a small, possibly insignificant negative trend towards the east-southeast. The temperatures at 15 km depth are estimated to be 190 °C beneath the zone of seamounts and 280 °C beneath the Voring Plateau.

Isotope analysis and heat flow measurements of Maria S. Merian cruise MSM21/4 on the western Svalbard margin

Methane hydrate is an ice-like substance that is stable at high-pressure and low temperature in continental margin sediments. Since the discovery of a large number of gas flares at the landward termination of the gas hydrate stability zone off Svalbard, there has been concern that warming bottom waters have started to dissociate large amounts of gas hydrate and that the resulting methane release may possibly accelerate global warming. Here, we can corroborate that hydrates play a role in the observed seepage of gas, but we present evidence that seepage off Svalbard has been ongoing for at least three thousand years and that seasonal fluctuations of 1-2°C in the bottom-water temperature cause periodic gas hydrate formation and dissociation, which focus seepage at the observed sites.

Photosynthesis and water relations of well-watered orange plants as affected by winter and summer conditions

The aim of this study was to evaluate how the summer and winter conditions affect the photosynthesis and water relations of well-watered orange trees, considering the diurnal changes in leaf gas exchange, chlorophyll (Chl) fluorescence, and leaf water potential (I) of potted-plants growing in a subtropical climate. The diurnal pattern of photosynthesis in young citrus trees was not significantly affected by the environmental changes when compared the summer and winter seasons. However, citrus plants showed higher photosynthetic performance in summer, when plants fixed 2.9 times more CO(2) during the diurnal period than in the winter season. Curiously, the winter conditions were more favorable to photosynthesis of citrus plants, when considering the air temperature (< 29 A degrees C), leaf-to-air vapor pressure difference (< 2.4 kPa) and photon flux density (maximum values near light saturation) during the diurnal period. Therefore, low night temperature was the main environmental element changing the photosynthetic performance and water relations of well-watered plants during winter. Lower whole-plant hydraulic conductance, lower shoot hydration and lower stomatal conductance were noticed during winter when compared to the summer season. In winter, higher ratio between the apparent electron transport rate and leaf CO(2) assimilation was verified in afternoon, indicating reduction in electron use efficiency by photosynthesis. The high radiation loading in the summer season did not impair the citrus photochemistry, being photoprotective mechanisms active. Such mechanisms were related to increases in the heat dissipation of excessive light energy at the PSII level and to other metabolic processes consuming electrons, which impede the citrus photoinhibition under high light conditions.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.