Transport of chlorinated dioxins and furans in soil columns: modeling pentachlorophenol pole-treating oil influence

Column experiments were conducted to validate a screening model predicting the influence of pentachlorophenol (PCP) pole-treating oil on the vertical migration of its impurities, chlorinated dioxins and furans (PCDD/Fs). PCP pole-treating oil (15 mL d⁻¹) and water (20 mL d⁻¹) were added daily to the top of sand and organic soil columns during 35 d. Column soil samples were analyzed to determine concentrations of hydrocarbons and PCDD/Fs at several depths in the columns (0-30 cm) and their evolution in time (7, 14, 21 and 35 d).The model predicted a significant vertical migration of PCDD/Fs due to the presence of oil as a free phase and PCDD/Fs were found in the different column layers at concentrations consistent with model predictions (same order of magnitude). Measured PCDD/Fs concentrations are in total disagreement with literature data and with model prediction in the absence of oil free phase, which implies PCDD/F properties alone cannot be used to predict their fate in the current context: the influence of PCP pole-treating oil must be accounted for to properly explain their migration.     

Growth performance of planted mangroves in the Philippines: revisiting forest management strategies

The effort toward restoring lost mangroves in the Philippines has been commendably immense, specifically during the past two decades. In light of such, it is important to evaluate outcomes and, where appropriate, apply the lessons learned to the current strategies in mangrove forest management. This article synthesizes the results from several research projects assessing the performance of planted mangroves across the country. Overall, there is a widespread tendency to plant mangroves in areas that are not the natural habitat of mangroves, converting mudflats, sandflats, and seagrass meadows into often monospecific Rhizophora mangrove forests. In these nonmangrove areas, the Rhizophora seedlings experienced high mortality. Of the few that survived (often through persistent and redundant replanting), the young Rhizophora individuals planted in these nonmangrove and often low intertidal zones had dismally stunted growth relative to the corresponding growth performance of individuals thriving at the high intertidal position and natural mangrove sites. From this evidence, this article argues that a more rational focus of the restoration effort should be the replanting of mangroves in the brackish-water aquaculture pond environments, the original habitat of mangroves. For such, a number of management options can be explored, the implementation of which will ultimately depend on the political will of local and national governments.     

Assessment of water quality parameters of the Harike wetland in India, a Ramsar site, using IRS LISS IV satellite data

This study aims at the classification and water quality assessment of Harike wetland (Ramsar site) in India using satellite images from the Indian Remote Sensing satellite, Resourcesat (IRS P6). The Harike wetland is a converging zone of two rivers, Beas and Sutlej. The satellite images of IRS Linear Imaging Self Scanner (LISS) IV multispectral sensor with three bands (green, red, and near infrared (NIR)) and a spatial resolution of 5.8 m were classified using supervised image classification techniques. Field points for image classification and water sampling were recorded using a Garmin eTrex Global Positioning System. The water quality parameters assessed were dissolved oxygen, conductivity, pH, turbidity, total and suspended solids (SS), chemical oxygen demand, and Secchi disk transparency (SDT). Correlations were established between turbidity and SS, SS and SDT, and total solids and turbidity. Using reflectance values from the green, red, and NIR bands, we then plotted the water quality parameters with the mean digital number values from the satellite imagery. The NIR band correlated significantly with the water quality parameters, whereas, using SDT values, it was observed that the green and the red reflectance bands were able to distinguish the waters from the two rivers, which have different water qualities.     

Effect of 2,4-D contamination on soil functional stability evaluated using the relative soil stability index (RSSI)

Soil functional stability is the capacity of soil functions to resist and recover from an environmental perturbation and can be used to evaluate soil health. It can be influenced by the presence of xenobiotics such as herbicides. The impact of a fresh 2,4-D contamination (36 mg kg(-1) dry soil) on soil functional stability was evaluated by comparing the capacity of soil enzyme activities to resist and recover from a heat perturbation for both a clean and 2,4-D-contaminated soil. The functional stabilities of the soils (uniform sands, pH 6.9, 7% (w/w) organic matter) were calculated using the relative soil stability index (RSSI). The RSSI scores indicate the proportion of potential enzyme activity the soil retains after a perturbation compared to the potential activity of an unperturbed soil. Six extra-cellular enzyme activities (acid and alkaline phosphatases, arylsulfatase, urease, protease and beta-glucosidase) were monitored in soil microcosms during a 15-day period. During this period, a 60 degrees C heat perturbation was applied to the soil for 24 h. The activities of arylsulfatase and protease were found to be the most stable following heat perturbation obtaining the highest RSSI scores (87% and 77%, respectively). Urease activity showed the lowest RSSI score (38%). Although all enzyme activities were inhibited by the presence of 2,4-D, the RSSI results indicated that contamination lowered the stability of only three enzyme activities (arylsulfatase, beta-glucosidase and urease). The RSSI adequately described resistance, recovery and recovery rate parameters and enabled differentiation between functional stabilities of clean and contaminated soil and between different soil types.     

Synthesis of zinc-carboxylate metal-organic frameworks for the removal of emerging drug contaminant (amodiaquine) from aqueous solution

We herein report the removal of amodiaquine, an emerging drug contaminant from aqueous solution using [Zn2(fum)2(bpy)] and [Zn4 O(bdc)3](fum = fumaric acid; bpy =4,4-bipyridine; bdc = benzene-1,4-dicarboxylate) metal–organic frameworks(MOFs) as adsorbents. The adsorbents were characterized by elemental analysis, Fourier transform infrared(FT-IR) spectroscopy, and powder X-ray diffraction(PXRD). Adsorption process for both adsorbents were found to follow the pseudo-first-order kinetics, and the adsorption equilibrium data fitted best into the Freundlich isotherm with the R~2 values of 0.973 and0.993 obtained for [Zn_2(fum)_2(bpy)] and [Zn_4 O(bdc)_3] respectively. The maximum adsorption capacities foramodiaquine in this study were found to be 0.478 and 47.62 mg/g on the[Zn_2(fum)_2(bpy)] and [Zn_4 O(bdc)_3] MOFs respectively, and were obtained at p H of 4.3 for both adsorbents. FT-IR spectroscopy analysis of the MOFs after the adsorption process showed the presence of the drug. The results of the study showed that the prepared MOFs could be used for the removal of amodiaquine from wastewater.     

Experimental investigation of adsorption capacity of anthill in the removal of heavy metals from aqueous solution

In the present work, the adsorption capacity of anthill was investigated as a low‐cost adsorbent to remove the heavy metal ions, lead (II) ion (Pb²⁺), and zinc (II) ion (Zn²⁺) from an aqueous solution. The equilibrium adsorption isotherms of the heavy metal ions were investigated under batch process. For the study we examined the effect of the solution's pH and the initial cations concentrations on the adsorption process under a fixed contact time and temperature. The anthill sample was characterized using a scanning electron microscope (SEM), X‐ray fluorescence (XRF), and Fourier transform infrared (FTIR) techniques. From the SEM analysis, structural change in the adsorbent was a result of heavy metals adsorption. Based on the XRF analysis, the main composition of the anthill sample was silica (SiO₂), alumina (Al₂O₃), and zirconia (ZrO₂). The change in the peaks of the spectra before and after adsorption indicated that there was active participation of surface functional groups during the adsorption process. The experimental data obtained were analyzed using 2‐ and 3‐parameter isotherm models. The isotherm data fitted very well to the 3‐parameter Radke–Prausnitz model. It was noted that Pb²⁺ and Zn²⁺ can be effectively removed from aqueous solution using anthill as an adsorbent.     

Health officials’ perceptions of and preparedness for the impacts of climate variability on human health in the Somali region of Ethiopia

A proactive strategy to respond effectively to health impacts related to climate variability, particularly within vulnerable populations, is of vital importance. Such a strategy can be attained if health officials have a deep understanding of how climate variability affects human health and if the resources available for the health care sector are sufficient. This study assessed the perceptions and preparedness of health officials toward climate variability and health impacts in the Somali region of Ethiopia. The resources available for the health care sector were also assessed. The results show that approximately 80% of health officials were aware of the relationship between climate variability and human health impacts, but the majority of them were unable to project the future trend of related health problems in the region. The results also show an inadequate availability of health care resources, particularly in regards to infrastructure, numbers of health professionals, and training on climate variability and health. The results further revealed problems with poor living conditions, such as access to sanitation and safe water, for the majority of people in the study area. Climate variability is thus one of the many factors exacerbating the increasing trend of human health problems in the Somali region. Besides improving training to increase health officials’ knowledge of climate variability and human health impacts, the government should also address other factors that currently hinder a successful response to increasing disease prevalence.     

Wetland Flowpaths Mediate Nitrogen and Phosphorus Concentrations across the Upper Mississippi River Basin

Eutrophication, harmful algal blooms, and human health impacts are critical environmental challenges resulting from excess nitrogen and phosphorus in surface waters. Yet we have limited information regarding how wetland characteristics mediate water quality across watershed scales. We developed a large, novel set of spatial variables characterizing hydrological flowpaths from wetlands to streams, that is, “wetland hydrological transport variables,” to explore how wetlands statistically explain the variability in total nitrogen (TN) and total phosphorus (TP) concentrations across the Upper Mississippi River Basin (UMRB) in the United States. We found that wetland flowpath variables improved landscape-to-aquatic nutrient multilinear regression models (from R² = 0.89 to 0.91 for TN; R² = 0.53 to 0.84 for TP) and provided insights into potential processes governing how wetlands influence watershed-scale TN and TP concentrations. Specifically, flowpath variables describing flow-attenuating environments, for example, subsurface transport compared to overland flowpaths, were related to lower TN and TP concentrations. Frequent hydrological connections from wetlands to streams were also linked to low TP concentrations, which likely suggests a nutrient source limitation in some areas of the UMRB. Consideration of wetland flowpaths could inform management and conservation activities designed to reduce nutrient export to downstream waters.     

Technological trends in nanosilica synthesis and utilization in advanced treatment of water and wastewater

Environmental Science and Pollution Research - Water and wastewater treatment applications stand to benefit immensely from the design and development of new materials based on silica nanoparticles...     

Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.