斜坡区和隆起区断裂密集带差异性及其对油气分布的控制作用

此文以霸县凹陷文安斜坡和饶阳凹陷留楚构造为研究对象,对比了斜坡区和隆起区断裂密集带的特征及其对不同构造部位油气分布的控制作用。在三维地震资料、钻井资料和已发现油气藏特征的基础上,利用断裂密集带识别方法和分类方案,识别出文安斜坡和留楚构造的断裂密集带,并对其进行了分类。对比两种构造部位断裂密集带发育的差异性及对油气分布的控制作用,认为隆起区(留楚构造)相对于斜坡区(文安斜坡)断裂密集带发育数量较少,规模大,斜坡区断裂密集带主要以顺向背形断裂密集带为主,而隆起区主要以屋脊背形断裂密集带为主,隆起区油气主要分布在顺向背形断裂密集带内,斜坡区主要分布在屋脊背形断裂密集带内部及靠近生烃中心的边部。     

Re-politicising water governance: exploring water re-allocations in terms of justice

Contemporary socio-economic transformations in South Asia are creating increasingly serious water problems (scarcity, flooding, pollution) and conflicts. Conflicts over water distribution, water-derived benefits, and risks often play out along axes of social differentiation like caste, wealth, and gender. Those with least power, rights, and voice suffer lack of access, exclusion, dispossession, and further marginalisation, resulting in livelihood insecurity or increased vulnerability to risks. In this paper we propose analysing these problems as problems of justice – problems of distribution, recognition, and political participation. Drawing on wider environmental justice approaches, a specific water justice focus needs to include both the specific characteristics of water as a resource and the access, rights, and equity dimensions of its control. We argue that recognising water problems as problems of justice requires a re-politicisation of water, as mainstream approaches to water resources, water governance, and legislation tend to normalise or naturalise their – basically political – distributional assumptions and implications. An interdisciplinary approach that sees water as simultaneously natural (material) and social is important here. We illustrate these conceptual and theoretical suggestions with evidence from India.     

Emissions of organic compounds and trace metals in fine particulate matter from motor vehicles: a tunnel study in Houston, Texas

Fine particulate matter (PM) samples collected in a highway tunnel in Houston, TX, were analyzed to quantify the concentrations of 14 n-alkanes, 12 polycyclic aromatic hydrocarbons, and nine petroleum biomarkers, as well as 21 metals, with the ultimate aim of identifying appropriate tracers for diesel engines. First, an exploratory multivariate dimensionality reduction technique called principal component analysis (PCA) was employed to identify all potential candidates for tracers. Next, emission indices were calculated to interpret PCA results physically. Emission indices of n-heneicosane, n-docosane, n-tricosane, n-tetracosane, n-pentacosane, fluoranthene, and pyrene were correlated highly and increased strongly with percentage carbon present in the tunnel emanating from diesel vehicles. This suggests that these organic compounds are useful molecular markers to separate emissions from diesel and gasoline engines. Additionally, the results are the first quantification of the metal composition of PM with aerodynamic diameters smaller than 2.5 microm (PM2.5) emissions from mobile sources in Houston. PCA of trace metal concentrations followed by emission index calculations revealed that barium in fine airborne particles can be linked quantitatively to diesel engine emissions, demonstrating its role as an elemental tracer for heavy-duty trucks.     

Changes in tissue cholesterol and serum cortisol level during four reproductive phases of the male freshwater fish, Notopterus notopterus

The tissue cholesterol and serum cortisol changes during four reproductive phases has been studied in the freshwater fish Notopterus notopterus of male sex during four phases, preparatory (January - March), prespawning (April - May), spawning (August - September) and post spawning (November - December). The cholesterol content of the testis and liver increased during preparatory phase and maximum content of cholesterol was during spawning phase. The serum cortisol estimated by radioimmunoassay (RIA) technique which indicated that the level of the hormone was high during pre-spawning and spawning phases compared to other two phases. The increase in cholesterol during preparatory and spawning phases may be because of increase in cortisol synthesis needed for testicular growth and spermetogenesis during these phases. The gonadosomatic index (GSI) also increased during these phases.     

Statistical analysis of the physico-chemical data on the coastal waters of Cochin

Measurements of temperature, salinity, dissolved oxygen, nitrogen as ammonia, nitrate and nitrite, and phosphate along with chlorophyll were carried out at three stations on the coastal waters of Cochin, south west India, at two-levels of the water column over a period of five years. The data set has been factorised using principal component analysis (PCA) for extracting linear relationships existing among a set of variables. A graphical display of the scores generated from the PCA was done by means of boxplots and biplots, which helped in the interpretation of the data. The major factors conditioning the system are related to the input of fresh water from the estuary of the Periyar river and the high organic load of the bottom sediment in the coastal area which results in a reducing environment, as reflected in the parameters of dissolved oxygen, ammoniacal-nitrogen and nitrite-nitrogen. Another factor which contributes to the variation in the system is related to the unloading activity in the port area. The present approach presents a logical way to interpret the complex data of the physico-chemical measurements.     

Role of cortisol on condition factor in the female freshwater fish, Notopterus notopterus during four reproductive phases

The condition of the female fish, Notopterus notopterus was studied during four phases of the reproductive cycle in control and after cortisol hormone treatment. The condition of the fish including condition factor (K) and somatic condition factor (Ks) was determined based on weight of the body, length of the fish and gonad weight. In control fish the condition of the fish improve during prespawning phase compared to other phases. The hormone cortisol level estimated by radioimmunoassay (RIA) technique was found to be increased in preparatory and decreased during prespawning phase, may be because of the hormone involvement in metabolic activity, vitellogenesis. In cortisol treatment, the condition of the fish decrease during prespawning phase, compared to other phase may be because of extra expenditure of energy for progressing reproductive activity such as vitellogenesis.     

Water quality and bacteriology in an aquaculture facility equipped with a new aeration system

The HOBAS aeration system was tested to compare changes in environmental and bacteriological parameters in ponds growing Penaeus monodon during a single production cycle. The stocking density in the aerated pond was doubled to 12 post-larvae (PL) m^???2 in contrast to the non-aerated pond with 6 (PL) m^???2. Microbial abundance in the ponds ranged between 10^5???6 cells ml^???1. Among the physiological groups of bacteria enumerated, the heterotrophs dominated with an abundance of 10⁴ CFU ml^???1. Of the nitrogen and sulfur cycle bacteria, the nitrifiers flourished in the aerated pond and could maintain ammonia-N concentration within permissible levels. Bacterial activity also maintained sulfide concentrations at <?0.03 mg l^???1. Non-aerated conditions promoted denitrification maintaining nitrate concentration between 0.32 and 0.98 μM NO₃ ^???-N l^???1. However, a marked increase in ammonium content was observed in the non-aerated pond at the end of the culture period. Thus in high-density ponds, the aerators served to stimulate bacterial growth and activity which consequently maintained the quality of the water to match that of low-density ponds. Accordingly, these aerators could be effectively used to sustain higher yields. The effluent from the aerated pond is less likely to alter the redox balance of the receiving waters.     

Comparison of microbial indicators under two water regimes in a soil amended with combined paper mill sludge and decomposed cow manure

An incubation study was conducted under laboratory conditions to compare the effects of soil amendment of combined paper mill sludge (PS) and decomposed cow manure (DCM) on selected microbial indicators. A lateritic soil (Typic Haplustalf) was amended with 0 (control), 20 or 80tha(-1) (wet weight) of PS or DCM. The amended soils were then adjusted to 60% water holding capacity (WHC) or submerged conditions, and incubated at 27 degrees C in dark for up to 120days (d). The microbial biomass C (MBC), the basal soil respiration and the enzyme activities of the beta-glucosidase, acid phosphatase and sulphatase were analyzed at day 15, 30, 45, 60 and 120. Compared to the unamended soil (control), the MBC, the basal soil respiration and the enzyme activities increased with the rate of PS and DCM. At similar rate, the DCM treatment increased significantly the MBC, the soil respiration and the enzyme activities compared to the PS treatment. Also, the water regimes affected the microbial activities. At 60% WHC, the MBC and soil respiration increased during the first 30d and decreased thereafter. The enzyme activities showed similar trends, where they increased for the first 60d, and decreased thereafter. In contrast, under submerged condition, the MBC and enzymes activities declined during 120d, whereas the soil respiration increased. Compared to the control, the used of PS and DCM had no negative impact of the soil microbial parameters, even at the highest application rate. Long-term field experiments are required to confirm these laboratory results.     

Assessment of groundwater quality: a fusion of geochemical and geophysical information via Bayesian neural networks

Deplorable quality of groundwater arising from saltwater intrusion, natural leaching and anthropogenic activities is one of the major concerns for the society. Assessment of groundwater quality is, therefore, a primary objective of scientific research. Here, we propose an artificial neural network-based method set in a Bayesian neural network (BNN) framework and employ it to assess groundwater quality. The approach is based on analyzing 36 water samples and inverting up to 85 Schlumberger vertical electrical sounding data. We constructed a priori model by suitably parameterizing geochemical and geophysical data collected from the western part of India. The posterior model (post-inversion) was estimated using the BNN learning procedure and global hybrid Monte Carlo/Markov Chain Monte Carlo optimization scheme. By suitable parameterization of geochemical and geophysical parameters, we simulated 1,500 training samples, out of which 50 % samples were used for training and remaining 50 % were used for validation and testing. We show that the trained model is able to classify validation and test samples with 85 % and 80 % accuracy respectively. Based on cross-correlation analysis and Gibb’s diagram of geochemical attributes, the groundwater qualities of the study area were classified into following three categories: “Very good”, “Good”, and “Unsuitable”. The BNN model-based results suggest that groundwater quality falls mostly in the range of “Good” to “Very good” except for some places near the Arabian Sea. The new modeling results powered by uncertainty and statistical analyses would provide useful constrain, which could be utilized in monitoring and assessment of the groundwater quality.