Environmental Science
D. Jaishree; P.T. Ravichandran; D.V. Thattai
Abstract
BACKGROUND AND OBJECTIVES: Studying the monthly variations in the surface features of the Bay of Bengal is a complex task that involves numerous large-scale ocean-atmosphere dynamics. This study identified the bay’s changing circulation patterns over recent decades as a crucial study area requiring ...
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BACKGROUND AND OBJECTIVES: Studying the monthly variations in the surface features of the Bay of Bengal is a complex task that involves numerous large-scale ocean-atmosphere dynamics. This study identified the bay’s changing circulation patterns over recent decades as a crucial study area requiring in-depth research. Understanding the changes in circulation patterns provides valuable insights into the Bay dynamics. It helps identify the potential impacts of climate change, ocean currents, and other factors on the bay’s ecosystem. This study aims to understand the seasonal variability of the Bay of Bengal’s surface circulation features using a high-resolution numerical Coastal and Regional Ocean Community simulations model. METHODS: To conduct the study in the Bay of Bengal, the Coastal and Regional Ocean Community model, a numerical ocean model, was utilized. The high-resolution numerical model for ocean circulation is three-dimensional and uses hydrostatic primitive equations in generalized curvilinear coordinates. Simulations were conducted over 8 years using a grid comprising 256 x 249 horizontal surface points to model a range of ocean-atmospheric parameters. This grid provided an approximate resolution of 10 kilometers.FINDINGS: The findings are based on the model’s enhanced performance compared to previous study results. It was observed that the sea surface temperature remains above 28 degrees Celsius throughout the bay except in winter. During the monsoon season, surface salinity was observed to be reduced in the Bay of Bengal’s northern region and western and eastern boundaries. Surface eddies along the western bay extend to deep waters before the onset of monsoon. The net heat flux in the bay has been determined as positive before monsoon, negative post-monsoon, and mixed during the monsoon season.CONCLUSION: This analysis focuses on the ocean surface layer with more prominent dynamics. Various surface parameters were calculated, and discussions on surface temperature, salinity, D20, D26, and net heat flux across seasons have been presented.
Environmental Management
B. Zaman; W. Oktiawan; M. Hadiwidodo; E. Sutrisno; P. Purwono
Abstract
BACKGROUND AND OBJECTIVES: Urban intensity and activities produce a large amount of biodegradable municipal solid waste. Therefore, biodrying processing was adopted to ensure the conversion into Refuse Derived Fuel and greenhouse gases.METHODS: This study was performed at a greenhouse, using six biodrying ...
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BACKGROUND AND OBJECTIVES: Urban intensity and activities produce a large amount of biodegradable municipal solid waste. Therefore, biodrying processing was adopted to ensure the conversion into Refuse Derived Fuel and greenhouse gases.METHODS: This study was performed at a greenhouse, using six biodrying reactors made from acrylic material, and equipped with digital temperature recording, blower, and flow meters. The variations in airflow (0, 2, 3, 4, 5, 6 L/min/kg) and the bulking agent (15%) were used to evaluate calorific value, degradation process and GHG emissions.FINDINGS: The result showed significant effect of airflow variation on cellulose content and calorific value. Furthermore, the optimum value was 6 L/min/kg, producing a 10.05% decline in cellulose content, and a 38.17% increase in calorific value. Also, the water content reduced from 69% to 40%. The CH4 concentration between control and biodrying substantially varied at 2.65 ppm and 1.51 ppm respectively on day 0 and at peak temperature. Morever, the value of N2O in each control was about 534.69 ppb and 175.48 ppb, while the lowest level was recorded after biodrying with 2 L/min/kg airflow.CONCLUSION: The calorific value of MSW after biodrying (refuse derived fuel) ranges from 4,713 – 6,265 cal/g. This is further classified in the low energy coal (brown coal) category, equivalent to <7,000 cal/g. Therefore, the process is proven to be a suitable alternative to achieve RDF production and low GHG emissions.
M. Mohammadi; A. Mohammadi Torkashvand; P. Biparva; M. Esfandiari
Abstract
Four diverse chlorides layered double hydroxides with diverse ratios, i.e. Mg-Al (3:1), Mg-Al (4:1), Zn-Al (4:1), and Zn-Al (3:1) LDHs, were prepared to evaluate their efficiency and selectivity towards nitrate removal from aquatic solutions. A batch experiment was done at the initial nitrate concentration ...
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Four diverse chlorides layered double hydroxides with diverse ratios, i.e. Mg-Al (3:1), Mg-Al (4:1), Zn-Al (4:1), and Zn-Al (3:1) LDHs, were prepared to evaluate their efficiency and selectivity towards nitrate removal from aquatic solutions. A batch experiment was done at the initial nitrate concentration of 5-1000 mg/L, pH 5 to 12, and contact time of 5-180 min. Isotherms of nitrate adsorption on LDHs, soil and soil-LDH mixtures were studied. Kinetics of adsorption, temperature effect, nitrate adsorption in nitrate adsorption, simulated soil solution and desorption on Mg-Al-LDH (4:1) were measured. At an optimum speed of 250 rpm, pH value of 7 and adsorbent dosage of 2 g/L, the amounts of nitrate adsorption on Mg-Al- LDH (3:1) and Mg-Zn-LDH (3:1) and also on Mg-Al- LDH (4:1) and Mg-Zn-LDH (4:1) were obtained after 30 and 60 min, respectively. Isotherm studies indicated that nitrate adsorption on soil, soil-LDH mixture, and LDH fitted Langmuir linear isotherm. The highest nitrate adsorption on Mg-Al-LDH (4:1) and a mixture of soil-Mg-Al-LDH (4:1) were 188.67 and 107.52 mg/g, respectively. Among the studied kinetic equations for nitrate adsorption on Mg-Al-LDH (4:1), the pseudo-second-order with R2=0.998 had the best fitness. Negative values of ∆H in different nitrate concentrations indicated the exothermic process of nitrate adsorption on Mg-Al-LDH (4:1). In the presence of other anions, Mg-Al-LDH (4:1) removed nitrate preferentially. Moreover, Mg-Al-LDH (4:1) could exchange nitrate 20 times in different concentrations with no reduction in its adsorption capacity.
I. Kayes; S.A. Shahriar; K. Hasan; M. Akhter; M.M. Kabir; M.A. Salam
Abstract
Meteorological parameters play a significant role in affecting ambient air quality of an urban environment. As Dhaka, the capital city of Bangladesh, is one of the air pollution hotspot among the megacities in the world, however the potential meteorological influences on criteria air pollutants for this ...
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Meteorological parameters play a significant role in affecting ambient air quality of an urban environment. As Dhaka, the capital city of Bangladesh, is one of the air pollution hotspot among the megacities in the world, however the potential meteorological influences on criteria air pollutants for this megacity are remained less studied. The objectives of this research were to examine the relationships between meteorological parameters such as daily mean temperature (o C), relative humidity (%) and rainfall (mm) and, the concentration of criteria air pollutants (SO2, CO, NOx, O3, PM2.5 and PM10) from January, 2013 to December, 2017. This study also focused on the trend analysis of the air pollutants concentration over the period. Spearman correlation was applied to illustrate the relationships between air pollutants concentration and temperature, relative humidity and rainfall. Multiple linear and non-linear regressions were compared to explore potential role of meteorological parameters on air pollutants' concentrations. Trend analysis resulted that concentration of SO2 is increasing in the air of Dhaka while others are decreasing. Most of the pollutants resulted negative correlation with atmospheric temperature and relative humidity, however, they showed variable response to seasonal variation of meteorological parameters. Regression analysis resulted that both the multiple non-linear and linear model performed similar for predicting concentrations of particulate matters but for gaseous pollutants both model performances were poor. This research is expected to contribute in improving the forecast accuracy of air pollution under variable meteorological parameters considering seasonal fluctuations.
