Hydroxychloroquine in COVID-19: therapeutic promises,current status,and environmental implications

Environmental Science and Pollution Research - The outbreak of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected the entire world with its infectious spread and...     

Identification of erosion-prone areas using morphometric parameters,land use land cover and multi-criteria decision-making method: geo-informatics approach

Environment, Development and Sustainability - Soil erosion is the main driving force of several devastating natural hazards in the complex mountainous terrain of the Himalayas where the Teesta...     

Stagnant surface water bodies (SSWBs) as an alternative water resource for the Chittagong metropolitan area of Bangladesh: physicochemical characterization in terms of water quality indices

The concern over ensuing freshwater scarcity has forced the developing countries to delve for alternative water resources. In this study, we examined the potential of stagnant surface water bodies (SSWBs) as alternative freshwater resources in the densely populated Chittagong metropolitan area (CMPA) of Bangladesh??where there is an acute shortage of urban freshwater supply. Water samples were collected at 1-month intervals for a period of 1 year from 12 stations distributed over the whole metropolis. Samples were analyzed for pH, water temperature (WTemp), turbidity, electrical conductivity (EC), total dissolved solids, total solids, total hardness, dissolved oxygen (DO), chloride, orthophosphates, ammonia, total coliforms (TC), and trace metal (Cd, Cr, Cu, Pb, As, and Fe) concentrations. Based on these parameters, different types of water quality indices (WQIs) were deduced. WQIs showed most of CMPA-SSWBs as good or medium quality water bodies, while none were categorized as bad. Moreover, it was observed that the minimal water quality index (WQI_m), computed using five parameters: WTemp, pH, DO, EC, and turbidity, gave a reliable estimate of water quality. The WQI_m gave similar results in 72% of the cases compared with other WQIs that were based on larger set of parameters. Based on our finding, we suggest the wider use WQI_m in developing countries for assessing health of SSWBs, as it will minimize the analytical cost to overcome the budget constraints involved in this kind of evaluations. It was observed that except turbidity and TC content, all other quality parameters fluctuated within the limit of the World Health Organization suggested standards for drinking water. From our findings, we concluded that if the turbidity and TC content of water from SSWBs in CMPA are taken care of, they will become good candidates as alternative water resources all round the year.     

Investigation of arsenic removal in batch wise water treatments by means of sequential hydride generation flow injection analysis

Arsenic water pollution is a big issue worldwide. Determination of inorganic arsenic in each oxidation state is important because As(III) is much more toxic than As(V). An automated arsenic measurement system was developed based on complete vaporization of As by a sequential procedure and collection/preconcentration of the vaporized AsH(3), which was subsequently measured by a flow analysis. The automated sensitive method was applied to monitoring As(III) and As(V) concentrations in contaminated water standing overnight. Behaviors of arsenics were investigated in different conditions, and unique time dependence profiles were obtained. For example, in the standing of anaerobic water samples, the As(III) concentration immediately began decreasing whereas dead time was observed in the removal of As(V). In normal groundwater conditions, most arsenic was removed from the water simply by standing overnight. To obtain more effective removal, the addition of oxidants and use of steel wools were investigated. Simple batch wise treatments of arsenic contaminated water were demonstrated, and detail of the transitional changes in As(III) and As(V) were investigated.     

Assessment of the sources of suspended particulate matter aerosol using US EPA PMF 3.0

The main purpose of this paper was to carry out a source apportionment of suspended particulate matter (SPM) samples using positive matrix factorization procedure. The central and local Government of Japan introduced strict emission regulations in 2002/10 and 2003/10, respectively, in curbing SPM pollution from major metropolitans. This paper also highlighted the impact of the measures taken by the central and local Government of Japan on the reduction of SPM and the contributions of sources. SPM samples were collected for 6 years starting from 1999 to 2005 at two sites, i.e., site A (urban) and site B (suburban) of Yokohama, Japan. Microwave digestion and inductively coupled plasma-mass spectroscopy (ICP-MS) were employed to measure Mg, Al, Ca, V, Cr, Mn, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Ag, Cd, Cs, Ba, Pb and Bi, while water soluble ions (Na⁺, NH₄  ⁺_{4}^{\ \,+}, K⁺, Ca^2 +, Mg^2 +, Cl⁻, NO₃  ^-_{3}^{\ \,-} and SO₄  ^2-)_{4}^{\ \,2-}) as well as carbonaceous mass (EC and OC) were analyzed using ion chromatograph and CHN analyzer, respectively. The sources identified at two sites were automobile, soil dust, marine aerosol, mixed sources, and secondarily formed aerosol. Also, source quantification was performed. Automobile and soil dust were striking contributors at site A. Automobile and soil dust of SPM aerosol might be produced from local origin at current study areas. Besides, Asian dust had an impact on high concentrations of SPM aerosol in some certain period of the year due to the outflows of East Asian emission. In contrast, secondary aerosol in the form of sulfate and ammonium as well as mixed sources (coal, long-transported Cs, and other unknown sources) were remarkable at site B. Stationary/industrial combustion has apparently more impact on the release of SPM components at site B than A. Automobile regulations in 2002 and 2003, respectively, resulted in reduction of SPM by 28% for site A and 16% for site B. There was also net reduction of automobile contribution at both sites due to the above measures being implemented.     

Chemometric application in identifying sources of organic contaminants in Langat river basin

Increasing urbanization and changes in land use in Langat river basin lead to adverse impacts on the environment compartment. One of the major challenges is in identifying sources of organic contaminants. This study presented the application of selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) to classify the pollution sources in Langat river basin based on the analysis of water and sediment samples collected from 24 stations, monitored for 14 organic contaminants from polycyclic aromatic hydrocarbons (PAHs), sterols, and pesticides groups. The CA and DA enabled to group 24 monitoring sites into three groups of pollution source (industry and urban socioeconomic, agricultural activity, and urban/domestic sewage) with five major discriminating variables: naphthalene, pyrene, benzo[a]pyrene, coprostanol, and cholesterol. PCA analysis, applied to water data sets, resulted in four latent factors explaining 79.0% of the total variance while sediment samples gave five latent factors with 77.6% explained variance. The varifactors (VFs) obtained from PCA indicated that sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol, and stigmastanol) are strongly correlated to domestic and urban sewage, PAHs (naphthalene, acenaphthene, pyrene, benzo[a]anthracene, and benzo[a]pyrene) from industrial and urban activities and chlorpyrifos correlated to samples nearby agricultural sites. The results demonstrated that chemometric techniques can be used for rapid assessment of water and sediment contaminations.     

Discriminant analysis for the prediction of sand mass distribution in an urban stormwater holding pond using simulated depth average flow velocity data

The approach of this paper is to predict the sand mass distribution in an urban stormwater holding pond at the Stormwater Management And Road Tunnel (SMART) Control Centre, Malaysia, using simulated depth average floodwater velocity diverted into the holding during storm events. Discriminant analysis (DA) was applied to derive the classification function to spatially distinguish areas of relatively high and low sand mass compositions based on the simulated water velocity variations at corresponding locations of gravimetrically measured sand mass composition of surface sediment samples. Three inflow parameter values, 16, 40 and 80 m³ s^?1, representing diverted floodwater discharge for three storm event conditions were fixed as input parameters of the hydrodynamic model. The sand (grain size?>?0.063 mm) mass composition of the surface sediment measured at 29 sampling locations ranges from 3.7 to 45.5 %. The sampling locations of the surface sediment were spatially clustered into two groups based on the sand mass composition. The sand mass composition of group 1 is relatively lower (3.69 to 12.20 %) compared to group 2 (16.90 to 45.55 %). Two Fisher’s linear discriminant functions, F ₁ and F ₂, were generated to predict areas; both consist of relatively higher and lower sand mass compositions based on the relationship between the simulated flow velocity and the measured surface sand composition at corresponding sampling locations. F ₁?=??9.405?+?4232.119?×?A???1795.805?×?B?+?281.224?×?C, and F ₂?=??2.842?+?2725.137?×?A???1307.688?×?B?+?231.353?×?C. A, B and C represent the simulated flow velocity generated by inflow parameter values of 16, 40 and 80 m³ s^?1, respectively. The model correctly predicts 88.9 and 100.0 % of sampling locations consisting of relatively high and low sand mass percentages, respectively, with the cross-validated classification showing that, overall, 82.8 % are correctly classified. The model predicts that 31.4 % of the model domain areas consist of high-sand mass composition areas and the remaining 68.6 % comprise low-sand mass composition areas.     

Physicochemical factors and sources of particulate matter at residential urban environment in Kuala Lumpur

Long-term measurements (2004–2011) of PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) and trace gases (carbon monoxide [CO], ozone [O₃], nitrogen oxide [NO], oxides of nitrogen [NO_x], nitrogen dioxide [NO₂], sulfur dioxide [SO₂], methane [CH₄], nonmethane hydrocarbon [NMHC]) have been conducted to study the effect of physicochemical factors on the PM₁₀ concentration. In addition, this study includes source apportionment of PM₁₀ in Kuala Lumpur urban environment. An advanced principal component analysis (PCA) technique coupled with absolute principal component scores (APCS) and multiple linear regression (MLR) has been applied. The average annual concentration of PM₁₀ for 8 yr is 51.3 ± 25.8 μg m^?3, which exceeds the Recommended Malaysian Air Quality Guideline (RMAQG) and international guideline values. Detail analysis shows the dependency of PM₁₀ on the linear changes of the motor vehicles in use and the amount of biomass burning, particularly from Sumatra, Indonesia, during southwesterly monsoon. The main sources of PM₁₀ identified by PCA-APCS-MLR are traffic combustion (28%), ozone coupled with meteorological factors (20%), and windblown particles (1%). However, the apportionment procedure left 28.0 μg m^?3, that is, 51% of PM₁₀ undetermined.

Implications: Air quality is always a top concern around the globe. Especially in the South Asian regions, measures are not yet sufficient; as revealed in our studies, the concentrations of particulate matters exceed the tolerable limits. Long-term data analysis and characterization of particular matters and their sources will aid the policy makers and the concerned authority to adapt measures and policies according to the circumstances. Additionally, similar intensive studies will give insight about future implications of air quality management.     

An Optimised Direct Lysis Method for Viral RNA Extraction and Detection of Foodborne Viruses on Fruits and Vegetables

Detection of norovirus (NoV) and hepatitis A virus (HAV) on fruits and vegetables using current standard methodologies can be inefficient. Method optimisat