Effect of application of ammonium thiosulphate on production and emission of methane in a tropical rice soil

Agricultural sources of atmospheric methane include flooded rice (Oryza sativa L.) paddies. However, certain soil nutrient management and cultural practices offer opportunities to reduce methane emissions. The effect of application of ammonium thiosulphate, a potential source of nitrogen and sulphur and also an inhibitor of nitrification and urease on methane production and emission from flooded alluvial (Typic Haplaquept) rice soil in India, was examined. Methane production and emission from control and urea-amended soil samples were almost identical. Application of ammonium thiosulphate to laboratory-incubated flooded soil (30 and 60 μg N g⁻¹ soil) and flooded rice fields (45.6 and 60 kg N ha⁻¹) effected a distinct inhibition of methane production and emission. Ammonium thiosulphate stimulated the population of sulphate-reducing bacteria (SRB) to a greater extent at 60 μg N g⁻¹ soil than at 30 μg N g⁻¹ soil. In ammonium thiosulphate-applied rice field plots, mean methane efflux decreased by about 38 and 60% at 45.6 and 60 kg N ha⁻¹, respectively, over that of control. Inhibition of methane production by ammonium thiosulphate is, at least in part, due to the stimulation of SRB. Results suggest the mitigation potential of ammonium thiosulphate on methane emission from flooded rice paddies.     

Supervised clustering for automated document classification and prioritization: a case study using toxicological abstracts

Machine learning and natural language processing algorithms are currently widely used to retrieve relevant documents in a variety of contexts, including literature review and systematic review. Supervised machine learning algorithms perform well in terms of retrieval metrics such as recall and precision, but require the use of a sizeable training dataset, which is typically expensive to develop. Unsupervised machine learning algorithms do not require a training dataset and may perform well in terms of recall, but are typically lower in precision, and do not offer a transparent means for decision-makers to justify selection choices. In this paper, we illustrate the use of a hybrid document classification method based on semi-supervised learning that we refer to as “supervised clustering.” We show that supervised clustering combines the ease of use of unsupervised algorithms with the retrieval efficiency and transparency of supervised algorithms. We demonstrate through simulations the high performance and unbiased predictions of supervised clustering when provided even with only minimal training data. We further propose the use of ensemble learning as a means to maximize retrieval efficiency and to prioritize the review of those documents that are not eliminated by the supervised clustering algorithm.     

Methodology for consequence analysis of LNG releases at deepwater port facilities

A methodology to perform consequence analysis associated with liquefied natural gas (LNG) for a deepwater port (DWP) facility has been presented. Analytical models used to describe the unconfined spill dynamics of LNG are discussed. How to determine the thermal hazard associated with a potential pool fire involving spilled LNG is also presented. Another hazard associated with potential releases of LNG is the dispersion of the LNG vapor. An approach using computational fluid dynamics tools (CFD) is presented. The CFD dispersion methodology is benchmarked against available test data. Using the proposed analysis approach provides estimates of hazard zones associated with newly proposed LNG deepwater ports and their potential impact to the public.     

Impact of urbanization on the groundwater regime in a fast growing city in central India

This paper describes the impact of urbanization on the groundwater regime in a fast growing city, Solapur, in central India, giving special emphasis on the management of the present and ultimate demand of water in 2,020 AD. The objective is to apprise the city planners and administrators of the effects of urbanization on the groundwater regime in a fast growing medium-sized city in a developing country where the infrastructure developments are not in conformity with the rapid growth in population. Solapur city with an area of 178.57 km2 receives a recharge of about 24 million m3 of groundwater from various sources annually. Reduction in recharge, as conventionally assumed due to the impact of urbanization, could not, however, be well established. Instead, there was a rise in recharge as water use in the city grew from time to time and more and more water was supplied to satisfy the human needs. Compared to mid-1970s, groundwater levels have increased within the main city area due to increased recharge and decreased groundwater abstraction. However, outside the main city area, there is a general decline in groundwater levels due to increased groundwater utilization for irrigation purposes. Groundwater quality deterioration has been highly localized. Water quality has deteriorated during the last 10 years, especially in dugwells, mainly due to misuse and disuse of these structures and poor circulation of groundwater. However, in case of borewells, comparison of the present water quality with that in mid-1970s and early 1980s does not show any perceptible change. Deeper groundwater tapped by borewells can still be used for drinking purposes with caution.     

Comparison of jatropha and karanja biofuels on their combustion characteristics

Biofuel blends produced from Jatropha (Jatropha curcas) and Karanja (Pongamia pinnata) oil were evaluated for their combustion properties. Two kinds of blends (regular diesel with Jatropha and Karanja oil) were prepared at 20% volume to the diesel and tested as alternative fuels in single cylinder (vertical), water-cooled, direct injection diesel engine at the rated speed of 1500 rpm. The performance of the engine in terms of thermal efficiency at full load for diesel was 30%. For Jatropha and Karanja biodiesel blends, the thermal efficiencies were 29.0% and 28.6%, respectively. The maximum cylinder pressure and ignition delay for biodiesel fuel blends are very close to that of regular diesel. Prolonged combustion was observed for Karanja oil blend in comparison to Jatropha oil blend. The combustion pattern also reveals the slow burning characteristics of vegetable oils and this study indicates that the blended biofuels have combustion characteristics that are similar to regular diesel fuels.     

Phase behaviors,fuel properties,and combustion characteristics of alcohol-vegetable oil-diesel microemulsion fuels

Biofuels are being considered as alternatives to fossil-based fuels due to depletion of petroleum-based reserves and pollutant emission concerns. Vegetable oils and bioalcohols have proven to be viable alternative fuels both with and without engine modification. However, high viscosity and low energy content are long-term operational problems with vegetable oils and bioalcohols, respectively. Therefore, vegetable oil-based microemulsification is being evaluated as a method to reduce the high viscosity of vegetable oils and enhance the miscibility of alcohol and oil phases. Studies have shown that microemulsification with different alcohols lead to varying fuel properties depending on their structure. The overall goal of this study was to formulate microemulsion fuels with single and mixed alcohol systems by determining the effects of water content, alcohol branching structure and carbon chain length on phase behaviors, fuel properties, and emission characteristics. It was found that microemulsion fuels using certain alcohols displayed favorable stability, properties, and emission characteristics. Flames of fuels with linear short-chain-length alcohols had larger near-burner blue regions and lower CO and soot emissions indicating the occurrence of more complete combustion. In addition to alcohol effects, the effect of vegetable oils, surfactants, and additives on emission characteristics were insightful in pursuit of appropriate microemulsion fuels as cleaner burning alternatives to both No.2 diesel and canola biodiesel.     

Optimizing removal of ibuprofen from water by magnetic nanocomposite using Box–Behnken design

Purpose  

The present research aims to optimize the removal of ibuprofen (IBP), a non-steroidal anti-inflammatory, analgesic, and antipyretic drug from the aqueous solution using a synthesized magnetic carbon–iron nanocomposite, and to investigate the individual and combined effects of the independent process variables.     

Seasonal Variations of PM10 and TSP in Residential and Industrial Sites in an Urban Area of Kolkata, India

The objective of the study is to investigate seasonal and spatial variations of PM₁₀ (particulate matter with aerodynamic diameter less than or equal to 10 μm) and TSP (total suspended particulate matter) of an Indian Metropolis with high pollution and population density from November 2003 to November 2004. Ambient concentration measurements of PM₁₀ and TSP were carried out at two monitoring sites of an urban region of Kolkata. Monitoring sites have been selected based on the dominant activities of the area. Meteorological parameters such as wind speed, wind direction, rainfall, temperature and relative humidity were also collected simultaneously during the sampling period from Indian Meteorological Department, Kolkata. The 24 h average concentrations of PM₁₀ and TSP were found in the range 68.2–280.6 μg/m³ and 139.3–580.3 μg/m³ for residential (Kasba) area, while 62.4–401.2 μg/m³ and 125.7–732.1 μg/m³ for industrial (Cossipore) area, respectively. Winter concentrations of particulate pollutants were higher than other seasons, irrespective of the monitoring sites. It indicates a longer residence time of particulates in the atmosphere during winter due to low winds and low mixing height. Spread of air pollution sources and non-uniform mixing conditions in an urban area often result in spatial variation of pollutant concentrations. The higher particulate pollution at industrial area may be attributed due to resuspension of road dust, soil dust, automobile traffic and nearby industrial emissions. Particle size analysis result shows that PM₁₀ is about 52% of TSP at residential area and 54% at industrial area.     

Further Results on Permit Markets with Market Power and Cheating

This paper examines a market for pollution permits in which one firm has market power and one or more firms is noncompliant. I show that the firm with market power may choose to hold more permits than it needs, effectively retiring permits from the market. I also show that some noncompliance may be socially desirable because it can mitigate the distortion caused by market power. Similarly, some degree of market power may be socially desirable because it can, in turn, mitigate the distortion caused by noncompliance.