Performance of photocatalytic reactors using immobilized TiO2 film for the degradation of phenol and methylene blue dye present in water stream

TiO2 thin film photocatalyst was successfully synthesized and immobilized on glass reactor tube using sol-gel method. The synthesized TiO2 coating was transparent, which enabled the penetration of ultra-violet (UV) light to the catalyst surface. Two photocatalytic reactors with different operating modes were tested: (a) tubular photocatalytic reactor with re-circulation mode and (b) batch photocatalytic reactor. A new proposed TiO2 synthesized film formulation of 1 titanium isopropoxide: 8 isopropanol: 3 acetyl acetone: 1.1 H2O: 0.05 acetic acid (in molar ratio) gave excellent photocatalytic activity for degradation of phenol and methylene blue dye present in the water. The half-life time, t1/2 of photocatalytic degradation of phenol was 56 min at the initial phenol concentration of 1000 microM in the batch reactor. In the tubular photocatalytic reactor, 5 re-circulation passes with residence time of 2.2 min (single pass) degraded 50% of 40-microM methylene blue dye. Initial phenol concentration, presence of hydrogen peroxide, presence of air bubbling and stirring speed as the process variables were studied in the batch reactor. Initial methylene blue concentration, pH value, light intensity and reaction temperature were studied as the process variables in the tubular reactor. The synthesized TiO2 thin film was characterized using SEM, XRD and EDX analysis. A comparative performance between the synthesized TiO2 thin film and commercial TiO2 particles (99% anatase) was evaluated under the same experimental conditions. The TiO2 film was equally active as the TiO2 powder catalyst.     

The individual and cumulative effect of brominated flame retardant and polyvinylchloride (PVC) on thermal degradation of acrylonitrile-butadiene-styrene (ABS) copolymer

Acrylonitrile-butadiene-styrene (ABS) copolymers without and with a polybrominated epoxy type flame retardant were thermally degraded at 450 degrees C alone (10 g) and mixed with polyvinylchloride (PVC) (8 g/2 g). Gaseous and liquid products of degradation were analysed by various gas chromatographic methods (GC with TCD, FID, AED, MSD) in order to determine the individual and cumulative effect of bromine and chlorine on the quality and quantity of degradation compounds. It was found that nitrogen, chlorine, bromine and oxygen are present as organic compounds in liquid products, their quantity depends on the pyrolysed polymer or polymer mixture. Bromophenol and dibromophenols were the main brominated compounds that come from the flame retardant. 1-Chloroethylbenzene was the main chlorine compound observed in liquid products. It was also determined that interactions appear at high temperatures during decomposition between the flame retardant, PVC and the ABS copolymer.     

Surfactant solubilization of hydrophobic compounds in soil and water

The soil/water partition coefficient (K_d) of hexachlorobenzene (HCB) ranged from 220 1/kg to 1800 1/kg for eight soils having a wide range of physico-chemical properties. K_d normalised to soil organic carbon (K_oc) was found to be 28000 ± 4800 1/kg. Anionic surfactant dodecylsulphate (DS) present at concentrations above the critical micellar concentration (CMC) caused reductions in the apparent soil/water partition coefficient (K_d ^*) in the range of 3–26 times for most soils and up to 36–91 times for sandy soils. Below CMC, at environmentally relevant surfactant concentrations, K_d ^* was reduced by a factor of 1–13. For clay and calcareous soils significant adsorption/complexation/precipitation of DS occurred. At the lowest DS concentration this produced a two-fold increase in K_d ^*. At increasing DS concentrations this effect was shielded by the solubihzing effect from DS. Monomer (K_mn) and micellar (K_mc) surfactant/water partition coefficients for HCB were determined to be, 980 ± 190 1/kg and 21000 ± 1600 1/kg, respectively.     

Interactive effects of ozone and powdery mildew (Sphaerotheca fuliginea) on bottle gourd (Lagenaria siceraria)

Interacting effects of ozone at 0.05, 0.1 and 0.2 ppm and powdery mildew infection were studied with respect to the growth, flowering and fruit-setting of bottle gourd, and ozone injury, fungal colonization, conidia size and germination. Intermittent exposure in closed-top chambers to ozone at 0.1 or 0.2 ppm, and infection by Sphaerotheca fulginea, each caused significant suppressions of plant growth, flowering and fruit-setting. Fungal colonization was increased by exposures to 0.05 ppm ozone, but decreased by 0.2 ppm ozone. Less browning and necrosis (symptoms of ozone phytotoxicity) appeared on the leaves of mildew-inoculated plants exposed to ozone at 0.1 and 0.2 ppm. Conidia collected from plants exposed to 0.1 and 0.2 ppm were smaller, contained fewer fibrosin bodies and showed poor germination in-vitro. Fumigations with ozone at 0.05 ppm increased the germination of conidia collected from the exposed plants or of the conidia directly exposed to ozone on glass slides in microgas exposure cabinets. Distortion and wall rupturing of the conidia were induced by exposure to ozone at 0.2 ppm for 12 h. Ozone at 0.05 ppm and S. fuliginea jointly suppressed the root and shoot growth of bottle gourd significantly more than the sum of individual effects (synergistic interaction). The fungus infection partially protected the plants from injury by ozone at 0.2 ppm, and exposure to ozone at 0.2 ppm inhibited fungal development. Antagonistic reductions of damage to bottle gourd growth by simultaneous mildew infection and ozone at 0.2 ppm were observed. The study revealed that powdery mildew infection may become severe on bottle gourd grown in areas polluted with mild level of ozone (0.05 ppm) whereas, at 0.1 ppm O₃ or more, the disease will be suppressed.     

Recent spatial gradients and time trends in Dhaka,Bangladesh, air pollution and their human health implications

Dhaka, the capital of Bangladesh, is among the most polluted cities in the world. This research evaluates seasonal patterns, day-of-week patterns, spatial gradients, and trends in PM_2.5 (<2.5 µm in aerodynamic diameter), PM₁₀ (<10 µm in aerodynamic diameter), and gaseous pollutants concentrations (SO₂, NO₂, CO, and O₃) monitored in Dhaka from 2013 to 2017. It expands on past work by considering multiple monitoring sites and air pollutants. Except for ozone, the average concentrations of these pollutants showed strong seasonal variation, with maximum during winter and minimum during monsoon, with the pollution concentration of PM_2.5 and PM₁₀ being roughly five- to sixfold higher during winter versus monsoon. Our comparisons of the pollutant concentrations with Bangladesh NAAQS and U.S. NAAQS limits analysis indicate particulate matter (PM_2.5 and PM₁₀) as the air pollutants of greatest concern, as they frequently exceeded the Bangladesh NAAQS and U.S. NAAQS, especially during nonmonsoon time. In contrast, gaseous pollutants reported far fewer exceedances throughout the study period. During the study period, the highest number of exceedances of NAAQS limits in Dhaka City (Darus-Salam site) were found for PM_2.5 (72% of total study days), followed by PM₁₀ (40% of total study days), O₃ (1.7% of total study days), SO₂ (0.38% of total study days), and CO (0.25% of total study days). The trend analyses results showed statistically significant positive slopes over time for SO₂ (5.6 ppb yr^?1, 95% confidence interval [CI]: 0.7, 10.5) and CO (0.32 ppm yr^?1, 95% CI: 0.01, 0.56), which suggest increase in brick kilns operation and high-sulfur diesel use. Though statistically nonsignificant annual decreasing slopes for PM_2.5 (?4.6 µg/m³ yr^?1, 95% CI: ?12.7, 3.6) and PM₁₀ (?2.7 µg/m³ yr^?1, 95% CI: ?7.9, 2.5) were observed during this study period, the PM_2.5 concentration is still too high (~ 82.0 µg/m³) and can cause severe impact on human health.

Implications: This study revealed key insights into air quality challenges across Dhaka, Bangladesh, indicating particulate matter (PM) as Dhaka’s most serious air pollutant threat to human health. The results of these analyses indicate that there is a need for immediate further investigations, and action based on those investigations, including the conduct local epidemiological PM exposure-human health effects studies for this city, in order to determine the most public health effective interventions.     

Changes in Hydrology of the Ganges Delta of Bangladesh and Corresponding Impacts on Water Resources

The Ganges Delta in Bangladesh is an example of water‐related catastrophes in a major rural river basin where limitations in quantity, quality, and timing of available water are producing disastrous conditions. Water availability limitations are modifying the hydrologic characteristics especially when water allocation is controlled from the upstream Farakka Barrage. This study presents the changes and consequences in the hydrologic regime due to climate‐ and human‐induced stresses. Flow duration curves (FDCs), rainfall elasticity, and temperature sensitivity were used to assess the pre‐ and post‐barrage water flow patterns. Hydrologic and climate indices were computed to provide insight on hydro‐climatic variability and trend. Significant increases in temperature, evapotranspiration, hot days, heating, and cooling degree days indicate the region is heading toward a warmer climate. Moreover, increase in high‐intensity rainfall of short duration is making the region prone to extreme floods. FDCs depict a large reduction in river flows between pre‐ and post‐barrage periods, resulting in lower water storage capacity. The reduction in freshwater flow increased the extent and intensity of salinity intrusion. This freshwater scarcity is reducing livelihood options considerably and indirectly forcing population migration from the delta region. Understanding the causes and directions of hydrologic changes is essential to formulate improve water resources management in the region.     

Assessing external factors on substitution of fossil fuel by biofuels: model perspective from the Nordic region

The aim of this study is to develop a theoretical model by which to demonstrate how taxes and subsidies work as external factors to substitute fossil fuel by a forest-based biofuel. For biofuels, this study predominantly considers solid-form biomass that generates electricity; for fossil fuels, it considers coal. The model results explicated with three states by using various numeric values taken from the literature. Three states are as follows: a situation without a tax and subsidy, a situation with a biofuel subsidy, and a situation with a biofuel subsidy and a fossil fuel tax. The results of the first state exemplify current fuel market situation; those of the second indicate that the aggregate demand for biofuel has shifted upwards by around 15 % and that substitution has increased by around 18 % due to biofuel subsidies being offered. Under the third state, aggregate biofuel demand has shifted upwards by around 19 %, reduced the demand for fossil fuels by around 13 %, and increased substitution by around 31 %. This state relates to a greater sense of social welfare than other two states. It is conceivable that the joint application of taxes and subsidies will succour biofuel to supplant fossil fuel in the near future.     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

Cadmium contamination in agricultural soils of Bangladesh and management by application of organic amendments: evaluation of field assessment and pot experiments

Environmental Geochemistry and Health - In recent years, cadmium (Cd) contamination in agricultural soils and its subsequent transfer to crops is one of the high-priority environmental and public...     

Analyses on phenological and morphological variations of mangrove forests along the southwest coast of Bangladesh

Drastic changes in river discharge and salinity levels are threatening the phenology and morphology of the coastal mangrove forests of the Sundarbans of Bangladesh. We have used AVHRR GIMMS (1985–2006) and MODIS (2005–2010) satellite Normalized Difference Vegetation Index (NDVI) data to identify the temporal variation of the phenology of the mangroves. Linear interpolation and Fourier-based adjustment were applied to remove noise from the NDVI time series. Then linear regression analysis on a single area (8 km ? 8 km) and a composite of 36 areas for three NDVI statistics the annual minimum, annual average, and annual maximum were performed--over the time periods 1985–1990, 1990–2000, 2000–2006 and 2005–2010 to identify possible functional changes in NDVI time series around the Sundarbans. Furthermore, we used fourteen LANDSAT images spanning the period 1989–2010 to estimate the spatiotemporal rate of shoreline changes over the three time periods 1989–2000, 2000–2006, and 2006–2010. A decreasing trend in the annual minimum NDVI was observed in most of the areas of the Sundarbans for the period 1990–2000. During the years 2000–2006, the trends of the three NDVI statistics became significantly positive, indicating an improvement of the mangrove phenology. In the period 2005–2010, a decreasing trend in all the NDVI variables was again dominant. The coast underwent rapid erosion from 1989–2000 and 2006–2010. However, the rate substantially declined between 2000 and 2006, when accretion was dominant. The advent of the upstream Farakka barrage caused a significant reduction in the Ganges-Gorai River discharge and increased the salinity in and around the Sundarbans. Our study concludes that this may be responsible for the degradation of mangrove phenology and accelerated erosion in the earlier and recent periods. In the interim, 2000–2006, improved river discharge and salinity levels due to the Ganges water sharing agreement (1996) and dredging of the Gorai River bed (1998–1999) enhanced the mangrove phenology and helped the coast to gain land.