Performance of a biogas upgrading process based on alkali absorption with regeneration using air pollution control residues

This work analyzes the performance of an innovative biogas upgrading method, Alkali absorption with Regeneration (AwR) that employs industrial residues and allows to permanently store the separated CO₂. This process consists in a first stage in which CO₂ is removed from the biogas by means of chemical absorption with KOH or NaOH solutions followed by a second stage in which the spent absorption solution is contacted with waste incineration Air Pollution Control (APC) residues. The latter reaction leads to the regeneration of the alkali reagent in the solution and to the precipitation of calcium carbonate and hence allows to reuse the regenerated solution in the absorption process and to permanently store the separated CO₂ in solid form. In addition, the final solid product is characterized by an improved environmental behavior compared to the untreated residues. In this paper the results obtained by AwR tests carried out in purposely designed demonstrative units installed in a landfill site are presented and discussed with the aim of verifying the feasibility of this process at pilot-scale and of identifying the conditions that allow to achieve all of the goals targeted by the proposed treatment. Specifically, the CO₂ removal efficiency achieved in the absorption stage, the yield of alkali regeneration and CO₂ uptake resulting for the regeneration stage, as well as the leaching behavior of the solid product are analyzed as a function of the type and concentration of the alkali reagent employed for the absorption reaction.     

Mediterranean Coastal Sand Dune Vegetation: Influence of Natural and Anthropogenic Factors

The aim of the present work was to assess the conservation status of coastal dune systems in Tuscany (Italy). Emphasis was given to the presence and abundance of plant communities identified as habitat in accordance with the Directive 92/43/EEC. Twenty transects perpendicular to the shoreline were randomly positioned on the whole coastal area (30 km in length) in order to sample the full spectrum of plant communities. Vegetation zonation and relationships with the most frequent disturbance factors in the study area—beach cleaning, coastline erosion, presence of paths and roads, bathing settlements and trampling—were investigated through principal coordinate analysis and canonical correspondence analysis. Natural factors, such as distance from the sea and total length, were also considered. Differences in the conservation status of the sites were found, ranging from the total disappearance of the foredune habitats to the presence of the complete psammophilous (sand-loving) plant communities. Erosion, trampling, and paths were found to be closely correlated with degradation and habitat loss. Furthermore, the overall plant species diversity of dunes was measured with NH_Dune, a modified version of the Shannon index; while the incidence of invasive taxa was calculated using N, a naturalness index. However, these diversity indices proved to be a weaker bioindicator of ecosystem integrity than habitat composition along transects. A possible strategy for the conservation and management of these coastal areas could be to protect the foredunes from erosion and limit trampling through the installation of footbridges or the use of appropriate fences.     

Some Interpolation Estimators in Environmental Risk Assessment for Spatially Misaligned Health Data

Ecological regression studies are widely used in geographical epidemiology to assess the relationships between health hazard and putative risk factors. Very often, health data are measured at an aggregate level because of confidentiality restrictions, while putative risk factors are measured on a different grid, i.e., independent (exposure) variable and response (counts) variable are spatially misaligned. To perform a regression of risk on exposure, one needs to realign the spatial support of the variables. Bayesian hierarchical models constitute a natural approach to the problem because of their ability to model the exposure field and the relationship between exposure and relative risk at different levels of the hierarchy, taking proper account of the variability induced by the covariate estimation. In the current paper, we propose two fully Bayesian solutions to the problem. The first one is based on the kernel-smoothing technique, while the second one is built on the tessellation of the study region. We illustrate our methods by assessing the relationship between exposure to uranium in drinkable waters and cancer incidence, in South Carolina (USA).     

Orchard management under the effects of climate change: implications for apple,plum, and almond growing

Environmental Science and Pollution Research - The authors analyzed certain species and varieties of fruit tree in which applied crop technology is used and also undergoes the effects of climate...     

Some characteristics of a plume from a point source based on analytical solution of the two-dimensional advection–diffusion equation

The moments of the concentration distribution obtained using a recent analytical solution of the steady-state two-dimensional advection–diffusion equation are presented. The solving methodology is the Generalized Integral Laplace Transform Technique, which allows obtaining a reliable solution of the advection–diffusion equation without any restrictive assumption about the eddy diffusivity coefficients and wind speed profiles. The first four moments and value and position of maximum ground level concentration are calculated. The concentration standard deviation is compared against the semi-empirical ones used in operative Gaussian models.     

A simple non-separable,non-stationary spatiotemporal model for ozone

The past two decades have witnessed an increasing interest in the use of space-time models for a wide range of environmental problems. The fundamental tool used to embody both the temporal and spatial components of the phenomenon in question is the covariance model. The empirical estimation of space-time covariance models can prove highly complex if simplifying assumptions are not employed. For this reason, many studies assume both spatiotemporal stationarity, and the separability of spatial and temporal components. This second assumption is often unrealistic from the empirical point of view. This paper proposes the use of a model in which non-separability arises from temporal non-stationarity. The model is used to analyze tropospheric ozone data from the Emilia-Romagna Region of Italy.     

Refuse derived soluble bio-organics enhancing tomato plant growth and productivity

Municipal bio-refuse (CVD), containing kitchen wastes, home gardening residues and public park trimmings, was treated with alkali to yield a soluble bio-organic fraction (SBO) and an insoluble residue. These materials were characterized using elemental analysis, potentiometric titration, and 13C NMR spectroscopy, and then applied as organic fertilizers to soil for tomato greenhouse cultivation. Their performance was compared with a commercial product obtained from animal residues. Plant growth, fruit yield and quality, and soil and leaf chemical composition were the selected performance indicators. The SBO exhibited the best performance by enhancing leaf chlorophyll content, improving plant growth and fruit ripening rate and yield. No product performance-chemical composition relationship could be assessed. Solubility could be one reason for the superior performance of SBO as a tomato growth promoter. The enhancement of leaf chlorophyll content is discussed to identify a possible link with the SBO photosensitizing properties that have been demonstrated in other work, and thus with photosynthetic performance.