Environmental Effectiveness of Swine Sewage Management: A Multicriteria AHP-Based Model for a Reliable Quick Assessment

Environmental issues related to swine production are still a major concern for the general public and represent a key challenge for the swine industry. The environmental impact of higher livestock concentration is particularly significant where it coincides with weaker policy standards and poor manure management. Effective tools for environmental monitoring of the swine sewage management process become essential for verifying the environmental compatibility of farming facilities and for defining suitable policies aimed at increasing swine production sustainability. This research aims at the development and application of a model for a quick assessment of the environmental effectiveness of the pig farming sewage management process. In order to define the model, multicriteria techniques, and in particular, Saaty’s analytic hierarchy process, were used to develop an iterative process in which the various key factors influencing the process under investigation were analyzed. The model, named EASE (Environmental Assessment of Sewages management Effectiveness), was optimized and applied to the Lake Trasimeno basin (Umbria, Italy), an area of high natural, environmental and aesthetic value. In this context, inadequate disposal of pig sewage represents a potential source of very considerable pollution. The results have demonstrated how the multicriteria model can represent a very effective and adaptable tool also in those decision-making processes aimed at the sustainable management of livestock production.     

Assessing Linkages in Stream Habitat,Geomorphic Condition,and Biological Integrity Using a Generalized Regression Neural Network

Watershed managers often use physical geomorphic and habitat assessments in making decisions about the biological integrity of a stream, and to reduce the cost and time for identifying stream stressors and developing mitigation strategies. Such analysis is difficult since the complex linkages between reach‐scale geomorphic and habitat conditions, and biological integrity are not fully understood. We evaluate the effectiveness of a generalized regression neural network (GRNN) to predict biological integrity using physical (i.e., geomorphic and habitat) stream‐reach assessment data. The method is first tested using geomorphic assessments to predict habitat condition for 1,292 stream reaches from the Vermont Agency of Natural Resources. The GRNN methodology outperforms linear regression (69% vs. 40% classified correctly) and improves slightly (70% correct) with additional data on channel evolution. Analysis of a subset of the reaches where physical assessments are used to predict biological integrity shows no significant linear correlation, however the GRNN predicted 48% of the fish health data and 23% of macroinvertebrate health. Although the GRNN is superior to linear regression, these results show linking physical and biological health remains challenging. Reasons for lack of agreement, including spatial and temporal scale differences, are discussed. We show the GRNN to be a data‐driven tool that can assist watershed managers with large quantities of complex, nonlinear data.     

Calcitic-based stones protection by a low-fluorine modified methacrylic coating

Environmental Science and Pollution Research - Atmospheric pollutants, such as NOx, SO2, and particulate matter, together with water percolation inside the stone pores, represent the main causes of...     

HEAVY METAL DISTRIBUTION AND SPECIATION IN THE NORTHERN ADRIATIC SEA

In the present study the concentrations of cobalt, copper, iron, manganese, zinc were analysed and the speciation of copper and zinc performed, with a summer and winter sampling, for two areas in the Northern Adriatic Sea and crossing at the farthest zones of the Po river-sea water interface. Results show that when salinity increases the concentrations of all investigated metals (with the exception of cobalt) present some degree of biogeochemical cycling. Copper is the element whose dissolved phase has the highest importance in metal transport across the salinity gradient. Results of speciation analysis demonstrate that the presence of excess amounts (5-8 fold) of unbound ligands confers a buffering capacity for potential inputs of dissolved metals into the Northern Adriatic Sea. The speciation of both copper and zinc in the dissolved phase was dominated by organic complexation.     

Heavy metal removal from industrial effluents by sorption on cross-linked starch: chemical study and impact on water toxicity

Batch sorption experiments using a starch-based sorbent were carried out for the removal of heavy metals present in industrial water discharges. The influence of contact time, mass of sorbent and pollutant load was investigated. Pollutant removal was dependent on the mass of sorbent and contact time, but independent of the contaminant load. The process was uniform, rapid and efficient. Sorption reached equilibrium in 60 min irrespective of the metal considered (e.g. Zn, Pb, Cu, Ni, Fe and Cd), reducing concentrations below those permitted by law. The material also removed residual turbidity and led to a significant decrease in the residual chemical oxygen demand (COD) present in the industrial water discharge. The germination success of lettuce (Lactuca sativa) was used as a laboratory indicator of phytotoxicity. The results show that the sorption using a starch-based sorbent as non-conventional material, is a viable alternative for treating industrial wastewaters.     

Simulating the fate of indigenous antibiotic resistant bacteria in a mild slope wastewater polluted stream

The fate of indigenous surface-water and wastewater antibiotic resistant bacteria in a mild slope stream simulated through a hydraulic channel was investigated in outdoor experiments.The effect of(i) natural(dark) decay,(ii) sunlight,(iii) cloudy cover,(iv) adsorption to the sediment,(v) hydraulic conditions,(vi) discharge of urban wastewater treatment plant(UWTP)effluent and(vii) bacterial species(presumptive Escherichia coli and enterococci) was evaluated.Half-life time(T1/2) of E. coli under sunlight was in the range 6.48–27.7 min(initial bacterial concentration of 10~5 CFU/mL) depending on hydraulic and sunlight conditions. E. coli inactivation was quite similar in sunny and cloudy day experiments in the early 2 hr, despite of the light intensity gradient was in the range of 15–59 W/m~2; but subsequently the inactivation rate decreased in the cloudy day experiment(T1/2= 23.0 min) compared to sunny day(T_(1/2)= 17.4 min). The adsorption of bacterial cells to the sediment(biofilm) increased in the first hour and then was quite stable for the remaining experimental time. Finally, when the discharge of an UWTP effluent in the stream was simulated, the proportion of indigenous antibiotic resistant E. coli and enterococci was found to increase as the exposure time increased, thus showing a higher resistance to solar inactivation compared to the respective total populations.