Seismic crustal structure between the Transylvanian Basin and the Black Sea, Romania

In order to study the lithospheric structure in Romania a 450 km long WNW–ESE trending seismic refraction project was carried out in August/September 2001. It runs from the Transylvanian Basin across the East Carpathian Orogen and the Vrancea seismic region to the foreland areas with the very deep Neogene Focsani Basin and the North Dobrogea Orogen on the Black Sea. A total of ten shots with charge sizes 300–1500 kg were recorded by over 700 geophones. The data quality of the experiment was variable, depending primarily on charge size but also on local geological conditions. The data interpretation indicates a multi-layered structure with variable thicknesses and velocities. The sedimentary stack comprises up to 7 layers with seismic velocities of 2.0–5.9 km/s. It reaches a maximum thickness of about 22 km within the Focsani Basin area. The sedimentary succession is composed of (1) the Carpathian nappe pile, (2) the post-collisional Neogene Transylvanian Basin, which covers the local Late Cretaceous to Paleogene Tarnava Basin, (3) the Neogene Focsani Basin in the foredeep area, which covers autochthonous Mesozoic and Palaeozoic sedimentary rocks as well as a probably Permo-Triassic graben structure of the Moesian Platform, and (4) the Palaeozoic and Mesozoic rocks of the North Dobrogea Orogen. The underlying crystalline crust shows considerable thickness variations in total as well as in its individual subdivisions, which correlate well with the Tisza-Dacia, Moesian and North Dobrogea crustal blocks. The lateral velocity structure of these blocks along the seismic line remains constant with about 6.0 km/s along the basement top and 7.0 km/s above the Moho. The Tisza-Dacia block is about 33 to 37 km thick and shows low velocity zones in its uppermost 15 km, which are presumably due to basement thrusts imbricated with sedimentary successions related to the Carpathian Orogen. The crystalline crust of Moesia does not exceed 25 km and is covered by up to 22 km of sedimentary rocks. The North Dobrogea crust reaches a thickness of about 44 km and is probably composed of thick Eastern European crust overthrusted by a thin 1–2 km thick wedge of the North Dobrogea Orogen.     

Linear regression models for estimating true subsurface resistivity from apparent resistivity data

Simple linear regression (SLR) models for rapid estimation of true subsurface resistivity from apparent resistivity measurements are developed and assessed in this study. The objective is to minimize the processing time and computer memory required to carry out inversion with conventional algorithms. The arrays considered are Wenner, Wenner–Schlumberger and dipole–dipole. The parameters investigated are apparent resistivity (\(\rho _a \)) and true resistivity (\(\rho _t\)) as independent and dependent variables, respectively. For the fact that subsurface resistivity is nonlinear, the datasets were first transformed into logarithmic scale to satisfy the basic regression assumptions. Three models, one each for the three array types, are thus developed based on simple linear relationships between the dependent and independent variables. The generated SLR coefficients were used to estimate \(\rho _t\) for different \(\rho _a\) datasets for validation. Accuracy of the models was assessed using coefficient of determination (\(R^{2})\), F-test, standard error (SE) and weighted mean absolute percentage error (wMAPE). The model calibration \(R^{2}\) and F-value are obtained as 0.75 and 2286, 0.63 and 1097, and 0.47 and 446 for the Wenner, Wenner–Schlumberger and dipole–dipole array models, respectively. The SE for calibration and validation are obtained as 0.12 and 0.13, 0.16 and 0.25, and 0.21 and 0.24 for the Wenner, Wenner–Schlumberger and dipole–dipole array models, respectively. Similarly, the wMAPE for calibration and validation are estimated as 3.27 and 3.49%, 3.88 and 5.72%, and 5.35 and 6.07% for the three array models, respectively. When compared with standard constraint least-squares (SCLS) inversion and Incomplete Gauss–Newton (IGN) algorithms, the SLR models were found to reduce about 80–96.5% of the processing time and memory space required to carry out the inversion with the SCLS algorithm. It is concluded that the SLR models can rapidly estimate \(\rho _t\) for the various arrays accurately.     

On the marine atmospheric boundary layer characteristics over Bay of Bengal and Arabian Sea during the Integrated Campaign for Aerosols,gases and Radiation Budget (ICARB)

Detailed measurements were carried out in the Marine Atmospheric Boundary Layer (MABL) during the Integrated Campaign for Aerosols, gases and Radiation Budget (ICARB) which covered both Arabian Sea and Bay of Bengal during March to May 2006. In this paper, we present the meteorological observations made during this campaign. The latitudinal variation of the surface layer turbulent fluxes is also described in detail.     

Predicting dissolved oxygen in the Chesapeake Bay: applications and implications

Eutrophic depletion of dissolved oxygen (DO) and its consequences for ecosystem dynamics have been a central theme of research, assessment and management policies for several decades in the Chesapeake Bay. Ongoing forecast efforts predict the extent of the summer hypoxic/anoxic area due to nutrient loads from the watershed. However, these models neither predict DO levels nor address the intricate interactions among various ecological processes. The prediction of spatially explicit DO levels in the Chesapeake Bay can eventually lead to a reliable depiction of the comprehensive ecological structure and functioning, and can also allow the quantification of the role of nutrient reduction strategies in water quality management. In this paper, we describe a three dimensional empirical model to predict DO levels in the Chesapeake Bay as a function of water temperature, salinity and dissolved nutrient concentrations (TDN and TDP). The residual analysis shows that predicted DO values compare well with observations. Nash–Sutcliffe efficiency (NSE) and root mean square error-observations standard deviation ratio (RSR) are used to evaluate the performance of the empirical model; the scores demonstrate the usability of model predictions (NSE, surface layer = 0.82–0.86; middle layer = 0.65–0.82; bottom layer = 0.70–0.82; RSR surface layer = 0.37–0.44; middle layer = 0.43–0.58 and bottom layer = 0.43–0.54). The predicted DO values and other physical outputs from downscaling of regional weather and climate predictions, or forecasts from hydrodynamic models, can be used to forecast various ecological components. Such forecasts would be useful for both recreational and commercial users of the Chesapeake Bay.     

Enhancement of Biogas Generation by Addition of Lipase in the Co‐Digestion of Tannery Solid Wastes

Co‐digestion studies were carried out for biogas generation using fleshings as the primary substrate and a mixture of primary and secondary sludge generated during the treatment of tannery wastewater as the co‐substrate. Steapsin, a commercial grade lipase, was added to enhance the hydrolysis in anaerobic co‐digestion. The lipase dosages used were ranging between 0.25 and 1.0 g for a volatile solids input of 7.5 g. The performance of the co‐digestion was assessed from the volume of biogas generated. Experimental results revealed an optimum lipase dosage of about 0.75 g. At this dosage, the biogas generation was observed to increase by about 15% compared to that in the control without adding lipase. Further, the digestion with lipase addition was observed faster since the digestion period was reduced about 30%. This means that the capacity of the digester could also be reduced about 30% leading to savings in its installation cost.     

Atmospheric Surface-Layer Response to the Annular Solar Eclipse of 15 January 2010 over Thiruvananthapuram,India

On 15 January 2010, Thiruvananthapuram in India (8.5°N, 76.9°E) witnessed one of the longest possible noontime annular solar eclipses spanning a period of about 7 min centred at 1314 local time. Here, we present a case study on the behaviour of the atmospheric surface layer by comparing the eclipse-induced observations with similar measurements recorded on cloud-free/clear-sky days. During the peak period of the eclipse, the incoming solar irradiance was reduced by 87% of its normal values, resulting in an air-temperature decrease near the surface of 1.2°C in association with a significant reduction in turbulent kinetic energy, momentum flux and sensible heat flux. The rate of instantaneous decay in solar radiation and sensible heat flux from the first contact of the eclipse to its annularity was greater than that seen during normal evening hours.     

An estimate of equilibrium sensitivity of global terrestrial carbon cycle using NCAR CCSM4

Increasing concentrations of atmospheric CO₂ influence climate, terrestrial biosphere productivity and ecosystem carbon storage through its radiative, physiological and fertilization effects. In this paper, we quantify these effects for a doubling of CO₂ using a low resolution configuration of the coupled model NCAR CCSM4. In contrast to previous coupled climate-carbon modeling studies, we focus on the near-equilibrium response of the terrestrial carbon cycle. For a doubling of CO₂, the radiative effect on the physical climate system causes global mean surface air temperature to increase by 2.14 K, whereas the physiological and fertilization on the land biosphere effects cause a warming of 0.22 K, suggesting that these later effects increase global warming by about 10 % as found in many recent studies. The CO₂-fertilization leads to total ecosystem carbon gain of 371 Gt-C (28 %) while the radiative effect causes a loss of 131 Gt-C (~10 %) indicating that climate warming damps the fertilization-induced carbon uptake over land. Our model-based estimate for the maximum potential terrestrial carbon uptake resulting from a doubling of atmospheric CO₂ concentration (285–570 ppm) is only 242 Gt-C. This highlights the limited storage capacity of the terrestrial carbon reservoir. We also find that the terrestrial carbon storage sensitivity to changes in CO₂ and temperature have been estimated to be lower in previous transient simulations because of lags in the climate-carbon system. Our model simulations indicate that the time scale of terrestrial carbon cycle response is greater than 500 years for CO₂-fertilization and about 200 years for temperature perturbations. We also find that dynamic changes in vegetation amplify the terrestrial carbon storage sensitivity relative to a static vegetation case: because of changes in tree cover, changes in total ecosystem carbon for CO₂-direct and climate effects are amplified by 88 and 72 %, respectively, in simulations with dynamic vegetation when compared to static vegetation simulations.