Source identification, contamination status and health risk assessment of heavy metals from road dusts in Dhaka, Bangladesh

In this study, concentrations of Cr, Mn, Ni, Cu, Zn, Cd and Pb were determined in road dusts collected from different locations in Dhaka to assess source, contamination status and health risk. Energy-dispersive X-ray fluorescence spectroscopy and energy-dispersive X-ray spectroscopy were used to determine Cr, Mn, Ni, Cu, Zn, Cd and Pb and their mean concentrations were 162.27 ± 29.46, 721.18 ± 180.14, 35.65 ± 12.55, 104.56 ± 128.33, 515.32 ± 321.90, BDL, and 342.82 ± 591.20 mg/kg, respectively. Among the heavy metals, highest concentrations of Cu, Zn and Pb were found at urban sites-7 (municipal waste dumping) and 8 (medical waste incineration). Highest concentration of Cr followed by Cu and Zn was found at site-5 (Tejgaon, urban). Principal component analysis revealed that anthropogenic activities are the potential sources for Cr, Ni, Cu, Zn and Pb while earth crust for Mn. Pollution index and pollution load index results suggested that all the sites were contaminated and/or degraded by Cr, Cu, Zn and Pb except sites-9 (urban), 10 (sub-urban), 11 (rural) while sites-7 and 8 (urban) were extremely degraded. For noncarcinogenic health risk, hazard quotient values for dermal were higher compared to that of inhalation/ingestion. Though hazard index values were less than 1 at all the sites, these were at least one order of magnitude higher for children group than that of adult group, thus the children group may face more noncarcinogenic health risk at sites-7 and 8. Values of incremental lifetime cancer risk were from 10⁻⁹ to 10⁻¹¹ showed no carcinogenic health risk by road dusts contaminated with the heavy metals.     

Insecticide substitutes for DDT to control mosquitoes may be causes of several diseases

Malaria continues to be a public health problem in Bangladesh, despite efforts in the 1960s to eradicate the vectors through the use of DDT. At one point, eradication of malaria was acclaimed but later on it reappeared. The use of DDT is no more legally allowed in Bangladesh, which has been officially replaced by a number organophosphates and/or synthetic pyrethroids and their combinations in addition to the integrated vector management (IVM) package. IVM being a community approach is still to go a long way to be mass popular. Adulticides, larvicides, residual sprays, mosquito coil, insecticide-impregnated curtain, aerosol, etc. still serve as the major weapons of mosquito control. Thus, mosquito control still mostly depends on chemical insecticides. Although the use of DDT is banned in Bangladesh, there are reports on its illegal use in different forms. Moreover, there is tons of leftover DDT in Bangladesh, which is likely to cause several diseases. As per one report, about 500 MTs of DDT stockpiles are lying in the Medical Sub-Depots at Chittagong for over a period of 26 years. DDT is a persistent organic pollutant pesticide, which can cause diseases like cancer, endocrine disorder, disruption of immune system, embryonic abnormality, reproductive disorder, etc. Other chemical insecticides, which are replacing DDT, are also not free of hazardous impacts. IVM thus appears to be a wise approach requiring concerted efforts for the management of mosquito to control malaria. Such an IVM comprises use of Bacillus thuringiensis Berliner var. israelensis, methoprene, biocontrol agents, cleaning of breeding sites, pyrethroid-impregnated curtain, etc. Therefore, a wise effort should be adopted to completely stop the use of DDT, eliminate its stockpiles wherever they are in Bangladesh and to popularise the IVM, not the chemicals-based alternatives throughout the country.     

Contrasting structure and composition of the understory in species-rich tropical rain forests

In large samples of trees > or = 1 cm dbh (more than 1 million trees and 3000 species), in six lowland tropical forests on three continents, we assigned species with >30 individuals to one of six classes of stature at maturity (SAM). We then compared the proportional representation of understory trees (1-2 cm dbh) among these classes. The understory of the three Asian sites was predominantly composed of the saplings of large-canopy trees whereas the African and American sites were more richly stocked with trees of the smaller SAM classes. Differences in class representation were related to taxonomic families that were present exclusively in one continent or another. Families found in the Asian plots but not in the American plot (e.g., Dipterocarpaceae, Fagaceae) were predominantly species of the largest SAM classes, whereas families exclusive to the American plots (e.g., Melastomataceae sensu stricto, Piperaceae, and Malvaceae [Bombacacoidea]) were predominantly species of small classes. The African plot was similar to Asia in the absence of those American families rich in understory species, while similar to America in lacking the Asian families rich in canopy species. The numerous understory species of Africa were chiefly derived from families shared with Asia and/or America. The ratio of saplings (1-2 cm dbh) to conspecific canopy trees (>40 cm dbh) was lower in American plots than in the Asian plots. Possible explanations for these differences include phenology, moisture and soil fertility regimes, phyletic constraints, and the role of early successional plants in forest development. These results demonstrate that tropical forests that appear similar in tree number, basal area, and the family taxonomy of canopy trees nonetheless differ in ecological structure in ways that may impact the ecology of pollinators, dispersers, and herbivores and might reflect fundamental differences in canopy tree regeneration.     

Graphical estimation of the dual-enzyme kinetic parameters for Cr(VI) reduction

Chromium(VI) (Cr(VI)) contamination of soil and groundwater is a major environmental concern. Bioreduction of Cr(VI) by Shewanella oneidensis MR-1 (MR-1) can be considered a feasible option to reduce the toxic and mobile Cr(VI) to the less toxic and less mobile chromium(III) (Cr(III)). The reaction rate expression for Cr(VI) reduction is nonlinear and the rate constants are evaluated by employing nonlinear optimization techniques. The outcome of the optimization techniques, in general, depends on the initial estimate of the kinetic parameters which is not always available. A graphical approach based on sound mathematical reasoning has been developed which is accurate, simpler to use, and can provide the best initial estimate for nonlinear optimization.     

Nanocarrier-mediated co-delivery systems for lung cancer therapy: recent developments and prospects

Environmental Chemistry Letters - Research has recently focused on combinational therapy using nanocarriers to overcome the obstacles associated with conventional therapy of lung cancer. The...     

Climate change and soil salinity: The case of coastal Bangladesh

This paper estimates location-specific soil salinity in coastal Bangladesh for 2050. The analysis was conducted in two stages: First, changes in soil salinity for the period 2001–2009 were assessed using information recorded at 41 soil monitoring stations by the Soil Research Development Institute. Using these data, a spatial econometric model was estimated linking soil salinity with the salinity of nearby rivers, land elevation, temperature, and rainfall. Second, future soil salinity for 69 coastal sub-districts was projected from climate-induced changes in river salinity and projections of rainfall and temperature based on time trends for 20 Bangladesh Meteorological Department weather stations in the coastal region. The findings indicate that climate change poses a major soil salinization risk in coastal Bangladesh. Across 41 monitoring stations, the annual median projected change in soil salinity is 39 % by 2050. Above the median, 25 % of all stations have projected changes of 51 % or higher.     

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.     

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.     

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.