Batch sorption dynamics and equilibrium for the removal of lead ions from aqueous phase using activated carbon developed from coffee residue activated with zinc chloride

Lignocellulosic materials are good precursors for the production of activated carbon. In this work, coffee residue has been used as raw material in the preparation of powder activated carbon by the method of chemical activation with zinc chloride for the sorption of Pb(II) from dilute aqueous solutions.The influence of impregnation ratio (ZnCl₂/coffee residue) on the physical and chemical properties of the prepared carbons was studied in order to optimize this parameter. The optimum experimental condition for preparing predominantly microporous activated carbons with high pore surface area (890 m²/g) and micropore volume (0.772 cm³/g) is an impregnation ratio of 100%. The developed activated carbon shows substantial capability to sorb lead(II) ions from aqueous solutions and for relative impregnation ratios of 75 and 100%, the maximum uptake is practically the same. Thus, 75% represents the optimal impregnation ratio.Batch experiments were conducted to study the effects of the main parameters such as contact time, initial concentration of Pb(II), solution pH, ionic strength and temperature. The maximum uptake of lead(II) at 25 °C was about 63 mg/g of adsorbent at pH 5.8, initial Pb(II) concentration of 10 mg/L, agitation speed of 200 rpm and ionic strength of 0.005 M. The kinetic data were fitted to the models of pseudo-first order and pseudo-second order, and follow closely the pseudo-second order model. Equilibrium sorption isotherms of Pb(II) were analyzed by the Langmuir, Freundlich and Temkin isotherm models. The Freundlich model gives a better fit than the others.Results from this study suggest that activated carbon produced from coffee residue is an effective adsorbent for the removal of lead from aqueous solutions and that ZnCl₂ is a suitable activating agent for the preparation of high-porosity carbons.     

Numerical analysis of water and solute transport in variably-saturated fractured clayey till

This study numerically investigates the influence of initial water content and rain intensities on the preferential migration of two fluorescent tracers, Acid Yellow 7 (AY7) and Sulforhodamine B (SB), through variably-saturated fractured clayey till. The simulations are based on the numerical model HydroGeoSphere, which solves 3D variably-saturated flow and solute transport in discretely-fractured porous media. Using detailed knowledge of the matrix, fracture, and biopore properties, the numerical model is calibrated and validated against experimental high-resolution tracer images/data collected under dry and wet soil conditions and for three different rain events. The model could reproduce reasonably well the observed preferential migration of AY7 and SB through the fractured till, although it did not capture the exact depth of migration and the negligible impact of the dead-end biopores in a near-saturated matrix. A sensitivity analysis suggests fast flow mechanisms and dynamic surface coating in the biopores, and the presence of a plough pan in the till.     

A Multilevel Model of the Impact of Farm‐Level Best Management Practices on Phosphorus Runoff1

Abstract: Multilevel or hierarchical models have been applied for a number of years in the social sciences but only relatively recently in the environmental sciences. These models can be developed in either a frequentist or Bayesian context and have similarities to other methods such as empirical Bayes analysis and random coefficients regression. In essence, multilevel models take advantage of the hierarchical structure that exists in many multivariate datasets; for example, water quality measurements may be taken from individual lakes, lakes are located in various climatic zones, lakes may be natural or man‐made, and so on. The groups, or levels, may effectively yield different responses or behaviors (e.g., nutrient load response in lakes) that often make retaining group membership more effective when developing a predictive model than when working with either all of the data together or working separately with the individuals. Here, we develop a multilevel model of the impact of farm level best management practices (BMPs) on phosphorus runoff. The result of this research is a model with parameters which vary with key practice categories and thus may be used to evaluate the effectiveness of these practices on phosphorus runoff. For example, it was found that the effect of fertilizer application rate on farm‐scale phosphorus loss is a function of the application method, the hydrologic soil group, and the land use (crop type). Further, results indicate that the most effective method for controlling fertilizer loss is through soil injection. In summary, the resultant multilevel model can be used to estimate phosphorus loss from farms and hence serve as a useful tool for BMP selection.     

Estimating human exposure to transport noise in central Dublin, Ireland

This paper reports on research conducted to determine estimates of the extent of environmental noise exposure from road transport on residents and workers in central Dublin, Ireland. The Harmonoise calculation method is used to calculate noise values for the study area while a Geographical Information System (GIS) is utilised as a platform upon which levels of noise exposure are estimated. Residential exposure is determined for L(den) and L(night) while worker exposure is determined for L(den). In order to analyse the potential of traffic management as a noise abatement measure, traffic was redirected from the main residential areas to alternative road links and the revised exposure levels were determined. The results show that the extent of noise exposure in Dublin is considerable, and in relative terms, it is worse for the night-time period. In addition, the results suggest also that traffic management measures have the potential to lead to significant reductions in the level of noise exposure provided that careful consideration is given to the impact of traffic flows on residential populations.     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

Vertical migration of radionuclides in undisturbed grassland soils

Literature data on numerical values obtained for the parameters of the two most popular models for simulating the migration of radionuclides in undisturbed soils have been compiled and evaluated statistically. Due to restrictions on the applicability of compartmental models, the convection–dispersion equation and its parameter values should be preferred. For radiocaesium, recommended values are derived for its effective convection velocity and dispersion coefficient. Data deficiencies still exist for radionuclides other than caesium and for soils of non-temperate environments.     

Lay concepts on CCS deployment in Switzerland based on qualitative interviews

Laypeople's acceptance and perception of Carbon Dioxide Capture and Storage (CCS) can have an influence on its political feasibility. It is important, therefore, to study how laypeople perceive CCS and which cognitions they hold with respect to this technique. We conducted in-depth interviews with laypeople (N = 16) to explore their mental concepts of CCS. Little knowledge about CCS was detected among laypeople. We also found that laypeople fear that a deployment of CCS could create incentives that would hinder a sustainable development of the energy economy. A misunderstanding of the concepts of hydro- and geostatic pressure, as well as a lack of knowledge about the physical–chemical properties of carbon dioxide seemed to trigger fundamental rejection of CCS among some laypeople. This qualitative study identifies concepts that underlie CCS perception, and these should be objects of future studies. We provide some suggestions for risk management and communication about CCS.     

Modelling plant species richness using functional groups

Conservation biologists increasingly rely on spatial predictive models of biodiversity to support decision-making. Therefore, highly accurate and ecologically meaningful models are required at relatively broad spatial scales. While statistical techniques have been optimized to improve model accuracy, less focus has been given to the question: How does the autecology of a single species affect model quality? We compare a direct modelling approach versus a cumulative modelling approach for predicting plant species richness, where the latter gives more weight to the ecology of functional species groups. In the direct modelling approach, species richness is predicted by a single model calibrated for all species. In the cumulative modelling approach, the species were partitioned into functional groups, with each group calibrated separately and species richness of each group was cumulated to predict total species richness. We hypothesized that model accuracy depends on the ecology of individual species and that the cumulative modelling approach would predict species richness more accurately. The predictors explained plant species richness by ca. 25%. However, depending on the functional group the deviance explained varied from 3 to 67%. While both modelling approaches performed equally well, the models of the different functional groups highly varied in their quality and their spatial richness pattern. This variability helps to improve our understanding on how plant functional groups respond to ecological gradients.     

Association of plutonium with sediments from the Ob and Yenisey Rivers and Estuaries

The present study applied sequential extraction techniques to investigate the binding and mobility of plutonium (Pu) in sediments from the rivers and estuaries of the Ob and Yenisey. As a study site, the Ob and Yenisey are particularly interesting as both rivers have weapons-grade Pu sources in their catchment areas, including the Russian Pu production and reprocessing plants at Mayak, Tomsk-7 and Krashnoyarsk, and the Semipalantinsk nuclear weapons testing site in Kazakhstan. Plutonium activity and ²⁴⁰Pu/²³⁹Pu ratios were determined using accelerator mass spectrometry (AMS). Sequential extractions showed that between 47 and 80% of the Pu in Yenisey River sediments and 35–53% of the Pu in soils around the Techa River are mobilized with weak oxidising agents, which can indicate that Pu is bound to organic material. In contrast, Pu in Ob and Yenisey Estuarine sediments was more strongly bound, with 60–100% being found in the HNO₃-extractable fraction. This change in speciation could reflect either that Pu bound to organic material in the Techa and Yenisey River sediments becomes more fixed to the sediments with time, or that organic-bound Pu is mobilized and released to the water when the sediments encounter the more saline water of the Ob and Yenisey estuaries. In general, ²⁴⁰Pu/²³⁹Pu ratios were relatively consistent between different extraction fractions, although, in whole sediments, an increase in ratio was observed with distance from the source. This reflects the increased influence of weapon fallout from catchment runoff within the river systems, as compared to the weapons-grade sources close to the production and reprocessing plants. Knowledge of Pu speciation in the Ob and Yenisey Rivers, and the processes controlling its behaviour in estuarine systems, can improve predictions of its transfer and subsequent environmental impact to Arctic Seas.