Risk analysis of an LPG storage facility in India

An assignment to carry out a hazard study and risk analysis of a gas processing complex has been described briefly, wherein well known procedures have been used to identify and investigate potential hazards. A method of avoiding unintentional overfilling of LPG storage tanks has been recommended, which utilizes the existing level control instruments.     

The CO2 abatement cost curve for the Thailand cement industry

The cement industry is one of the largest carbon dioxide (CO₂) emitters in the Thai industry. The cement sector accounted for about 20,633 kilotonnes (ktonnes) CO₂ emissions in 2005 in Thailand. A bottom-up CO₂ abatement cost curve (ACC) is constructed in this study for the Thai cement industry to determine the potentials and costs of CO₂ abatement, taking into account the costs and CO₂ abatement of different technologies. The period of 2010–2025 is chosen as the scenario period. We analyzed 41 CO₂ abatement technologies and measures for the cement industry. Using the bottom-up CO₂ ACC model, the cost-effective annual CO₂ abatement potential for the Thai cement industry during the 15 year scenario period (2010–2025) is equal to 3095 ktonnes CO₂/year. This is about 15% of the Thai cement industry’s total CO₂ emissions in 2005. The total technical annual CO₂ abatement potential is 3143 ktonnes CO₂/year, which is about 15.2% of the Thai cement industry’s total CO₂ emissions in 2005. We also conducted a sensitivity analysis for the discount rate parameter.     

Ploidy-, gender-, and dose-dependent alteration of selected biomarkers in Clarias gariepinus treated with benzo[a]pyrene

Naturally-occurring and artificially-induced polyploids have been documented in various fish species but to date no comparison has been reported of the impacts of ploidy on fish biomarker responses to organic pollutants. This study describes effects of ploidy, gender, and dose on biliary fluorescent aromatic compound (FAC) concentrations, hepatic ethoxyresorufin-O-deethylase (EROD) and glutathione S-transferase (GST) activities in one of the most commonly cultured warm-water species, the African catfish Clarias gariepinus. Recently matured male and female diploid and triploid fish were intraperitoneally (i.p.) injected with 0, 5 or 25 mg/kg benzo[a]pyrene (BaP) and liver and gallbladder were sampled 48 hr later. No significant differences were found between ploidies in bile concentrations of 7,8 dihydrodiolbenzo[a]pyrene (7,8D BaP), 1-hydroxybenzo[a]pyrene (1-OH BaP) or 3-hydroxybenzo[a]pyrene (3-OH BaP). However, concentrations of the biliary FACs did differ between males and females at different dose of injection with generally higher concentrations in females at the low dose of BaP and higher concentrations in males at the higher BaP concentration. Hepatic EROD activity did not exhibit gender-dependent difference, whereas it was significantly higher in triploids than diploids. GST activities were not significantly influenced by any of the tested factors. This work advanced our understanding of the role of ploidy, gender, and dose in biotransformation of pollutants in fish.     

Uncertainty-based quantitative assessment of sustainability for higher education institutions

Evaluation of sustainability in various facets of life is gaining increasing importance. Traditionally, different multi-criteria decision-making methods have been used for sustainability assessment. “Sustainability” can be a qualitative concept, and as such several researchers have attempted fuzzy logic for the quantitative assessment of sustainability. This paper outlines a new evaluation model based on fuzzy multi-criteria decision-making. The model is tested for sustainability assessment of higher education institutions (HEIs). It is based on a driving force–pressure–state–exposure–effect–action (DPSEEA) framework and is called uncertainty-based DPSEEA-Sustainability index Model (uD-SiM). The uD-SiM is a causality-based model in which the sustainability index is an outcome of nonlinear impacts of sustainability indicators in different stages of DPSEEA. The percent contribution of driving forces on the sustainability index of HEI is investigated using sensitivity analysis. The study reveals that education in sustainability and global and local research trends are the major driving forces for achieving sustainability in HEI, followed by financial and economic growth rate, social equity, energy requirements rate, and institutional enhancement, in descending order. The results of uD-SiM were found to be more realistic and rational than our earlier proposed approach, D-SiM.     

Gaseous and particulate emissions from thermal power plants operating on different technologies

This paper presents the assessment of gaseous and particulate emissions from thermal power plants operating on different combustion technologies. Four thermal power plants operating on heavy furnace oil were selected for the study, among which three were based on diesel engine technology, while the fourth plant was based on oil-fired steam turbine technology. The stack emissions were monitored for critical air pollutants carbon monoxide, carbon dioxide, oxides of nitrogen, sulfur dioxide, particulate matter, lead, and mercury. The pollutant emissions were measured at optimum load conditions for a period of 6 months with an interval of 1 month. The results of stack emissions were compared with National Environmental Quality Standards of Pakistan and World Bank guidelines for thermal power plants, and few parameters were found higher than the permissible limits of emissions. It was observed that the emissions carbon monoxide, oxides of nitrogen, and particulate matters from diesel engine-based power plants were comparatively higher than the turbine-based power plants. The emissions of sulfur dioxide were high in all the plants, even the plants with different technologies, which was mainly due to high sulfur contents in fuel.     

Synthesis of TiO2 nanoparticles in different thermal conditions and modeling its photocatalytic activity with artificial neural network

Titanium dioxide (TiO₂) nanoparticles were prepared by sol gel route. The preparation parameters were optimized in the removal of 4-nitrophenol (4-NP). All catalysts were analyzed by X-ray diffraction (XRD) and scanning electron microscopy (SEM). An artificial neural network model (ANN) was developed to predict the photocatalytic removal of 4-NP in the presence of TiO₂ nanoparticles prepared under desired conditions. The comparison between the predicted results by designed ANN model and the experimental data proved that modeling of the removal process of 4-NP using artificial neural network was a precise method to predict the extent of 4-NP removal under different conditions.