Fluoride removal and its impact on oral health in Sri Lanka's dry zone: Discussion and recommendation

Fifty percent of the dry zone areas in Sri Lanka have fluoride levels above 1 ppm. This paper discusses the ground conditions and recommends an appropriate range of fluoride in drinking water which can support preventive practices for improving the oral health of children 8-years old and younger. In efforts to address the Chronic Kidney Disease of Unknown etiology (CKDU), water treatment to reduce contaminant level in potable water has been implemented. Such treatment would also remove fluoride and has resulted in potable water with various fluoride levels, depending on concentrations in the raw water. While it is important to reduce fluoride levels, it is important to have appropriate residual levels for prevention of dental caries. It needs, however, to be noted fluoride in excess can cause dental fluorosis. In Sri Lanka's dry zone areas increasing prevalence of dental fluorosis with decreasing prevalence of dental caries has been noted. Consumption of tea and powdered milk could increase total intake of fluoride. Fluoridated toothpaste, when used properly, may, however, result in negligible intake of fluoride. Sri Lanka's hot tropical climate which results in substantial intake of fluids reinforces the need to consider reduction in water fluoride. Consideration of local studies and international standards indicate fluoride levels should be in the range of 0.225–0.500 ppm. In the range of 0.225–0.500 ppm, the prevalence of dental fluorosis and caries was only 14% and 8%, respectively, in an endemic district. When fluoride levels are above 0.500 ppm, the issue of dental fluorosis shall need to be addressed. When levels are below 0.225 ppm, oral health care services shall need to be directed at preventing dental caries.     

Static and Dynamic Behavior of Fibrous Polymeric Composite Materials at Different Environmental Conditions

The study of static and dynamic behavior of environmentally conditioned fibre reinforced polymeric (FRP) composites is necessary and crucial to examine the durability, reliability and sustainability of these noble materials. FRP composites are being used all around the globe and substituting the conventional materials, starting from mini toys to large aerospace components. Present review has introduced to accumulate and understand the disseminate literature in concentrating the significance of understanding the static and dynamic behavior of FRPs with changing environmental conditionings (hygrothermal, low and high temperature, salt solution, freeze thaw, UV light) and with the interaction of different nano-fillers. Their stability and integrity in diverse service environments may be reformed by their reactions against different nature of loadings i.e. static or dynamic and the components such as fibre, matrix and fibre/matrix interfaces in those environments. The static and dynamic states of loading may come with a possible weaker region to encounter the durability and integrity of the composites. To understand the exact failure modes that correlates the position of environmentally conditioned interfaces and dynamic state of loadings, thus confusing the estimation of its overall performance and mechanical behavior. Interface reliability and durability is vital since in-service environments the degradation in the interfacial region leads to complete composite failure. Therefore, the study of combined effects of various in-service environmental conditions and the role of static and dynamic behavior on the interface will be a crucial part related to the multiaxial dynamic states of failures occurring in FRP’s.     

Balancing the energy demand by a resource circulation project in Daejeon,Korea

Demand for sustainable renewable energy is on an increase worldwide, whereas the supply is limited. This paper analyses the feasibility of generating electricity and supplying the surplus steam to Daeduk Industrial Complex, by incinerating the combustible municipal waste generated in Daejeon Metropolitan City. The economic feasibility of surplus biogas generated from the anaerobic digestion of food waste and food waste leachate has been analysed. This study estimated resource circulation facility to supply 23,200 m³/day of biogas generated to Daejeon Combined Heat and Power plant. By 2023, it is expected to supply 25.7 tons of steam per hour all year round. The additional steam demand in Daeduk Industrial Complex is estimated as 101,537 tons/year. Surplus biogas will be supplied through an additional 960-m new installation. The cost of biogas is estimated at 30% of the unit biogas production cost. Daejeon Combined Heat and Power plant expects to make 60% additional profit, and Daeduk Industrial Complex and the communities nearby expect to achieve 10% cost savings. It also reduces the dependence of energy on fossil fuels, contributes to national environmental energy policy in reduction in greenhouse gases, creates competitiveness in local business and reduces corporate tax and generates revenue.     

Landslide probability mapping by considering fuzzy numerical risk factor (FNRF) and landscape change for road corridor of Uttarakhand,India

Landslide poses severe threats to the natural landscape of the Lesser Himalayas and the lives and economy of the communities residing in that mountainous topography. This study aims to investigate whether the landscape change has any impact on landslide occurrences in the Kalsi-Chakrata road corridor by detailed investigation through correlation of the landslide susceptibility zones and the landscape change, and finally to demarcate the hotspot villages where influence of landscape on landslide occurrence may be more in future. The rational of this work is to delineate the areas with higher landslide susceptibility using the ensemble model of GIS-based multi-criteria decision making through fuzzy landslide numerical risk factor model along the Kalsi-Chakrata road corridor of Uttarakhand where no previous detailed investigation was carried out applying any contemporary statistical techniques. The approach includes the correlation of the landslide conditioning factors in the study area with the changes in land use and land cover (LULC) over the past decade to understand whether frequent landslides have any link with the physical and hydro-meteorological or, infrastructure, and socioeconomic activities. It was performed through LULC change detection and landslide susceptibility mapping (LSM), and spatial overlay analysis to establish statistical correlation between the said parameters. The LULC change detection was performed using the object-oriented classification of satellite images acquired in 2010 and 2019. The inventory of the past landslides was formed by visual interpretation of high-resolution satellite images supported by an intensive field survey of each landslide area. To assess the landslide susceptibility zones for 2010 and 2019 scenarios, the geo-environmental or conditioning factors such as slope, rainfall, lithology, normalized differential vegetation index (NDVI), proximity to road and land use and land cover (LULC) were considered, and the fuzzy LNRF technique was applied. The results indicated that the LULC in the study area was primarily transformed from forest cover and sparse vegetation to open areas and arable land, which is increased by 6.7% in a decade. The increase in built-up areas and agricultural land by 2.3% indicates increasing human interference that is continuously transforming the natural landscape. The landslide susceptibility map of 2019 shows that about 25% of the total area falls under high and very high susceptibility classes. The result shows that 80% of the high landslide susceptible class is contained by LULC classes of open areas, scrubland, and sparse vegetation, which point out the profound impact of landscape change that aggravate landslide occurrence in that area. The result acclaims that specific LULC classes, such as open areas, barren-rocky lands, are more prone to landslides in this Lesser Himalayan road corridor, and the LULC-LSM correlation can be instrumental for landslide probability assessment concerning the changing landscape. The fuzzy LNRF model applied has 89.6% prediction accuracy at 95% confidence level which is highly satisfactory. The present study of the connection of LULC change with the landslide probability and identification of the most fragile landscape at the village level has been instrumental in delineation of landslide susceptible areas, and such studies may help the decision-makers adopt appropriate mitigation measures in those villages where the landscape changes have mainly resulted in increased landslide occurrences and formulate strategic plans to promote ecologically sustainable development of the mountainous communities in India's Lesser Himalayas.

     

Potential use of Caulerpa fastigiata biomass for removal of lead: kinetics, isotherms, thermodynamic, and characterization studies

The present study attempts to analyze the biosorption trend of biosorbent Caulerpa fastigiata (macroalgae) biomass for removal of toxic heavy metal ion Pb (II) from solution as a function of initial metal ion concentration, pH, temperature, sorbent dosage, and biomass particle size. The sorption data fitted with various isotherm models and Freundlich model was the best one with correlation coefficient of 0.999. Kinetic study results revealed that the sorption data on Pb (II) with correlation coefficient of 0.999 can best be represented by pseudo-second-order. The biosorption capacity (q _e ) of Pb (II) is 16.11?±?0.32 mg g^?1 on C. fastigiata biomass. Thermodynamic studies showed that the process is exothermic (ΔH° negative). Free energy change (ΔG°) with negative sign reflected the feasibility and spontaneous nature of the process. The SEM studies showed Pb (II) biosorption on selective grains of the biosorbent. The FTIR spectra indicated bands corresponding to –OH, COO^?, –CH, C?=?C, C?=?S, and –C–C– groups were involved in the biosorption process. The XRD pattern of the C. fastigiata was found to be mostly amorphous in nature.     

Biosorption of arsenic in drinking water by submerged plant: Hydrilla verticilata

To evaluate the biosorption efficacy of submerged aquatic plant Hydrilla verticilata for arsenic uptake from drinking water. H. verticillata, a submerged aquatic plant was utilized successfully for arsenic uptake from aqueous solution. Batch studies with various parameters viz. pH, sorbent dose, contact time, initial metal ion concentration, and temperature were carried out. Data were utilized to plot Lagergren graph along with pseudo-second-order graphs for kinetic studies to estimate the removal efficacy and to determine the nature of reaction. Scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) have been performed for characterization of metals on biomass. The study showed 96.35 % maximum absorption of arsenic by H. verticilata at initial concentration of 100 ppb with 0.5 g of biomass/100 ml for 5 h contact time at pH?6.0 with 150 rpm agitation rate. Data followed Langmuir isotherm showing sorption to be monolayer on homogeneous surface of biosorbent. The negative values of ΔG° indicated spontaneous nature; whereas ΔH° indicates exothermic nature of system and negative value of ?S° entropy change correspond to a decrease in the degree of freedom to the adsorbed species followed by pseudo-second-order adsorption kinetics. FTIR and SEM results showed apparent changes in functional group regions after metal chelation and the changes in surface morphology of biosorbent. This is a comparatively more effective, economic, easily available, and environmentally safe source for arsenic uptake from solution due to its high biosorption efficacy than other biosorbents already used.     

Two‐dimensional transport of lactate‐modified nanoscale iron particles in porous media

This study investigates the two‐dimensional transport of nanoscale iron particles (NIP) and lactate‐modified NIP (LMNIP) in homogeneous and heterogeneous porous media under typical pressurized groundwater flow conditions. A two‐dimensional bench‐scale test setup was developed and a series of experiments was conducted simulating homogeneous sand profile and two‐layer profile with two different sands. NIP and LMNIP at a concentration of 4 g/L were prepared in electrolyte simulating groundwater conditions and were injected at the inlet of the test setup under different pressure gradients (0.5. 0.8, 1, and 2 pounds per square inch). During the testing, effluent was collected and its volume and nanoiron concentrations were measured. At the end of the testing, soil cores were obtained at different distances from the inlet and were used to measure nanoiron concentrations and magnetic susceptibility values. Results showed that the transport of NIP and LMNIP was enhanced by increased pressure gradient. LMNIP transport occurred more uniformly as compared to bare NIP. The iron concentrations decreased with distance from the inlet to the outlet and increased from the top to the bottom of the test cell. The data indicate that, as the particles were transported, they underwent aggregation and sedimentation, which resulted in the observed non‐uniform spatial distribution of iron. The NIP and LMNIP transported through the high‐porosity and high‐permeability soil layer in the heterogeneous soil profile, implying that the transport occurred predominantly along the path of least resistance for the flow. Magnetic susceptibility values are found to have good correlation with the iron content in the soil and are helpful to characterize the transport of NIP and LMNIP. Overall, this study shows that the non‐uniform distribution of NIP and LMNIP occurs under two‐dimensional transport conditions and the soil heterogeneities can significantly impact the transport of NIP and LMNIP. The design of field delivery systems should consider such conditions and optimize the pressurized injection systems. © 2011 Wiley Periodicals, Inc.     

Constitutive model for municipal solid waste incorporating mechanical creep and biodegradation-induced compression

A constitutive model is proposed to describe the stress–strain behavior of municipal solid waste (MSW) under loading using the critical state soil mechanics framework. The modified cam clay model is extended to incorporate the effects of mechanical creep and time dependent biodegradation to calculate total compression under loading. Model parameters are evaluated based on one-dimensional compression and triaxial consolidated undrained test series conducted on three types of MSW: (a) fresh MSW obtained from working phase of a landfill, (b) landfilled waste retrieved from a landfill after 1.5 years of degradation, and (c) synthetic MSW with controlled composition. The model captures the stress–strain and pore water pressure response of these three types of MSW adequately. The model is useful for assessing the deformation and stability of landfills and any post-closure development structures located on landfills.     

Fire risk evaluation using multicriteria analysis—a case study

Forest fires are one of the major causes of ecological disturbance and environmental concerns in tropical deciduous forests of south India. In this study, we use fuzzy set theory integrated with decision-making algorithm in a Geographic Information Systems (GIS) framework to map forest fire risk. Fuzzy set theory implements classes or groupings of data with boundaries that are not sharply defined (i.e., fuzzy) and consists of a rule base, membership functions, and an inference procedure. We used satellite remote sensing datasets in conjunction with topographic, vegetation, climate, and socioeconomic datasets to infer the causative factors of fires. Spatial-level data on these biophysical and socioeconomic parameters have been aggregated at the district level and have been organized in a GIS framework. A participatory multicriteria decision-making approach involving Analytical Hierarchy Process has been designed to arrive at a decision matrix that identified the important causative factors of fires. These expert judgments were then integrated using spatial fuzzy decision-making algorithm to map the forest fire risk. Results from this study were quite useful in identifying potential “hotspots” of fire risk, where forest fire protection measures can be taken in advance. Further, this study also demonstrates the potential of multicriteria analysis integrated with GIS as an effective tool in assessing “where and when” forest fires will most likely occur.