Dynamic modelling for cork boiling wastewater treatment at pilot plant scale

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.     

Recovery of yttrium from fluorescent powder of cathode ray tube,CRT: Zn removal by sulphide precipitation

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%.     

Application of a Random Forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy

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.     

A decision-support system in ICZM for protecting the ecosystems: integration with the habitat directive

This paper describes a decision-support system based on landscape ecology and focused on the study of ecosystems’ health. System capabilities are illustrated with three cases of integrated coastal zone management (ICZM), in the Adriatic Sea (Italy): the lagoon of Venice and the Rimini and Ancona coastal areas. Indicators and indices are developed with a focus on sub-regional and local problems in coastal management, with a multi-scale approach based on landscape and seascape ecology. Land-use changes of the coastal areas were detected by analyzing two sets of satellite images. Indices combining satellite imagery, socio-economic and environmental indicators, and landscape and seascape maps were created, showing ecological changes, habitat loss and gaps in conservation policy. The approach used provides means for the identification of conflicts and for the assessment of sustainability. Results show that the lagoon of Venice plays an important role in mitigating and compensating the impacts of human activities, and needs to be protected and restored. The Rimini area shows high ecological footprint and development-intensity and low biocapacity. The Ancona area needs the protection of its natural coastal space from potential sources of anthropogenic impacts to maintain its sustainability. A model of environment changes is critical for formulating effective environmental policies and management strategies. The developed decision-support system provides a suitability map per each area analyzed, which can be used in order to maximize different policy objectives and reduce coastal conflicts.     

Sampling approaches to predict urban street noise levels using fixed and temporary microphones

Requirements for static (prediction of L(den) and diurnal averaged noise pattern) and dynamic (prediction of 15 min and 60 min evolution of L(Aeq) and statistical levels L(A90,)L(A50) and L(A10)) noise level monitoring are investigated in this paper. Noise levels are measured for 72 consecutive days at 5 neighboring streets in an inner-city noise measurement network in Gent, Flanders, Belgium. We present a method to make predictions based on a fixed monitoring station, combined with short-term sampling at temporary stations. It is shown that relying on a fixed station improves the estimation of L(den) at other locations, and allows for the reduction of the number of samples needed and their duration; L(den) is estimated with an error that does not exceed 1.5 dB(A) to 3.4 dB(A) according to the location, for 90% of the 3 × 15 min samples. Also the diurnal averaged noise pattern can be estimated with a good accuracy in this way. It was shown that there is an optimal location for the fixed station which can be found by short-term measurements only. Short-term level predictions were shown to be more difficult; 7 day samples were needed to build models able to estimate the evolution of L(Aeq,60min) with a RMSE ranging between 1.4 dB(A) and 3.7 dB(A). These higher values can be explained by the very pronounced short-term variations appearing in typical streets, which are not correlated between locations. On the other hand, moderately accurate predictions can be achieved, even based on short-term sampling (a 3 × 15 minute sampling duration seems to be sufficient for many of the accuracy goals set related to static and dynamic monitoring). Finally, the method proposed also allows for the prediction of the evolution of statistical indicators.     

Top-down control inhibits spatial self-organization of a patterned landscape

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.     

A robust-design formulation of the incidence function model of metapopulation dynamics applied to two species of rails

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.     

城乡融合评价研究综述：内涵辨识、理论认知与体系重构

科学的城乡融合评价是城乡融合工作的重要环节,是建立健全城乡融合体制机制的基础。以“内涵辨识—理论认知—体系重构”为逻辑主线,从城乡融合的概念内涵、基础理论、评价指标、评价方法、评价尺度及演化机理等方面,开展城乡融合评价综述。研究表明：学界对城乡融合概念与内涵的认识基本一致,且已有一定理论基础;城乡融合评价指标选取呈现多维化、多属性化特征,但指标体系构建尚未突破静态性层面;定量评价方法较为单一;研究尺度整体偏向中宏观,缺少微观视角下的量化以及不同融合模式对比研究;城乡融合的时空分异格局及其机理研究亟待进一步深化。对此,提出了以下五点展望：（1）加强基础理论体系建设,完善系统研究框架构建;（2）优化多维评价指标体系,识别城乡融合发展模式;（3）深化城乡要素流动机制,推动城乡空间均衡发展;（4）加强微观尺度细节挖掘,健全城乡融合推进机制;（5）强化数字经济赋能作用,创新城乡高质量融合发展机制。