Solar photo-Fenton process has been extensively reported to be highly efficient in the remediation of complex industrial wastewater containing several families of pollutants such as pharmaceuticals, dyes, pesticides, derivatives of wine, etc. Moreover, solar photo-Fenton mathematical modelling regarded as a powerful tool for scaling-up and process control purposes is hindered by the complexity and variability of its reaction mechanism which depends on the particular wastewater under study. In this work, non-biodegradable cork boiling wastewater has been selected as a case study for solar photo-Fenton dynamic modelling by using MATLAB® software. First of all physic-chemical pretreatment was applied attaining chemical oxygen demand (COD) reductions between 43 and 70 % and total suspended solid (TSS) reductions between 23 % and 59 %. After solar photo-Fenton treatment, COD decreased between 45 and 90 % after consumptions of H2O2 varying around 1.9 and 2.4 g/L. Individual calibration of the semi-empirical model by using experimental results made it possible to perfectly predict hydrogen peroxide variations throughout the treatment. It must be highlighted that slight deviations between predictions and experimental data must be attributed to important changes in wastewater characteristics. 相似文献
This work is focused on the recovery of yttrium and zinc from fluorescent powder of cathode ray tube (CRT). Metals are extracted by sulphuric acid in the presence of hydrogen peroxide. Leaching tests are carried out according to a 22 full factorial plan and the highest extraction yields for yttrium and zinc equal to 100% are observed under the following conditions: 3 M of sulphuric acid, 10% v/v of H2O2 concentrated solution at 30% v/v, 10% w/w pulp density, 70 °C and 3 h of reaction.Two series of precipitation tests for zinc are carried out: a 22 full factorial design and a completely randomized factorial design. In these series the factors investigated are pH of solution during the precipitation and the amount of sodium sulphide added to precipitate zinc sulphide. The data of these tests are used to describe two empirical mathematical models for zinc and yttrium precipitation yields by regression analysis. The highest precipitation yields for zinc are obtained under the following conditions: pH equal to 2–2.5% and 10–12% v/v of Na2S concentrated solution at 10% w/v. In these conditions the coprecipitation of yttrium is of 15–20%.Finally further yttrium precipitation experiments by oxalic acid on the residual solutions, after removing of zinc, show that yttrium could be recovered and calcined to obtain the final product as yttrium oxide. The achieved results allow to propose a CRT recycling process based on leaching of fluorescent powder from cathode ray tube and recovery of yttrium oxide after removing of zinc by precipitation. The final recovery of yttrium is 75–80%. 相似文献
Pepper mild mottle virus (PMMoV), a plant pathogenic virus belonging to the family Virgoviridae, has been proposed as a potential viral indicator for human faecal pollution in aquatic environments. The present study investigated the occurrence, amount and diversity of PMMoV in water environments in Italy. A total of 254 water samples, collected between 2017 and 2019 from different types of water, were analysed. In detail, 92 raw sewage, 32 treated sewage, 16 river samples, 9 estuarine waters, 20 bathing waters, 67 groundwater samples and 18 drinking waters were tested. PMMoV was detected in 79% and 75% of untreated and treated sewage samples, respectively, 75% of river samples, 67% and 25% of estuarine and bathing waters and 13% of groundwater samples. No positive was detected in drinking water. The geometric mean of viral concentrations (genome copies/L) was ranked as follows: raw sewage (2.2 × 106) > treated sewage (2.9 × 105) > river waters (6.1 × 102) > estuarine waters (4.8 × 102) > bathing waters (8.5 × 101) > groundwater (5.9 × 101). A statistically significant variation of viral loads could be observed between raw and treated sewage and between these and all the other water matrices. PMMoV occurrence and viral loads did not display seasonal variation in raw sewage nor correlation with faecal indicator bacteria in marine waters and groundwater. This study represents the first report on the occurrence and quantification PMMoV in different water environments in Italy. Further studies are required to evaluate the suitability of PMMoV as a viral indicator for human faecal pollution and for viral pathogens in waters.
Regular, self-organized spatial patterns in primary producers have been described in a wide range of ecosystems and are predicted to affect community production and resilience. Although consumers are abundant in most systems, the effect of trophic interactions on pattern formation in primary producers remains unstudied. We studied the effects of top-down control by herbivores on a self-organized landscape of regularly spaced, diatom-covered hummocks alternating with water-filled hollows on an intertidal mudflat in The Netherlands. Spatial patterns developed during spring but were followed by a rapid collapse in summer, leading to a flat landscape with low diatom densities and little variation in sediment bed level. This dramatic decline co-occurred with a gradual increase of benthic herbivores. A manipulative field experiment, where benthic herbivores were removed from the sediment, revealed that both diatom growth and hummock formation were inhibited by the activity of benthic herbivores. Our study provides clear evidence of top-down control of spatial self-organized patterns by benthic herbivores within a biological-geomorphic landscape. 相似文献
The incidence function model (IFM) uses area and connectivity to predict metapopulation dynamics. However, false absences and missing data can lead to underestimates of the number of sites contributing to connectivity, resulting in overestimates of dispersal ability and turnovers (extinctions plus colonizations). We extend estimation methods for the IFM by using a hierarchical Bayesian model to account both for false absences due to imperfect detection and for missing data due to sites not surveyed in some years. We compare parameter estimates, measures of metapopulation dynamics, and forecasts using stochastic patch occupancy models (SPOMs) among three IFM models: (1) a Bayesian formulation assuming no false absences and omitting site-year combinations with missing data; (2) a hierarchical Bayesian formulation assuming no false absences but incorporating missing data; and (3) a hierarchical Bayesian formulation allowing for imperfect detection and incorporating missing data. We fit the models to multiyear data sets of occupancy for two bird species that differ in body size and presumed dispersal ability but inhabit the same network of sites: the small Black Rail (Laterallus jamaicensis) and the medium-sized Virginia Rail (Rallus limicola). Incorporating missing data affected colonization parameters and led to lower estimates of dispersal ability for the Black Rail. Detection rates were high for the Black Rail in most years but moderate for the Virginia Rail. Incorporating imperfect detection resulted in higher occupancy and lower turnover rates for both species, with largest effects for the Virginia Rail. Forecasts using SPOMs were sensitive to both missing data and false absences; persistence in models assuming no false absences was more optimistic than from robust models. Our results suggest that incorporating false absences and missing data into the IFM can improve (1) estimates of dispersal ability and the effect of connectivity on colonization, (2) the scaling of extinction risk with patch area, and (3) forecasts of occupancy and turnover rates. 相似文献
We present a modelling framework that combines machine learning techniques and Geographic Information Systems to support the management of an important aquaculture species, Manila clam (Ruditapes philippinarum). We use the Venice lagoon (Italy), the first site in Europe for the production of R. philippinarum, to illustrate the potential of this modelling approach. To investigate the relationship between the yield of R. philippinarum and a set of environmental factors, we used a Random Forest (RF) algorithm. The RF model was tuned with a large data set (n = 1698) and validated by an independent data set (n = 841). Overall, the model provided good predictions of site-specific yields and the analysis of marginal effect of predictors showed substantial agreement among the modelled responses and available ecological knowledge for R. philippinarum. The most influent environmental factors for yield estimation were percentage of sand in the sediment, salinity, and water depth. Our results agree with findings from other North Adriatic lagoons. The application of the fitted RF model to continuous maps of all the environmental variables allowed estimates of the potential yield for the whole basin. Such a spatial representation enabled site-specific estimates of yield in different farming areas within the lagoon. We present a possible management application of our model by estimating the potential yield under the current farming distribution and comparing it to a proposed re-organization of the farming areas. Our analysis suggests a reduction of total yield is likely to result from the proposed re-organization. 相似文献