An experimental study on fermentative H2 production from food waste as affected by pH

Batch dark fermentation experiments were performed on food waste and mixtures of food waste and wastewater activated sludge to evaluate the influence of pH on biological H₂ production and compare the process performance with and without inoculum addition. The effect of a preliminary thermal shock treatment of the inoculum was also investigated as a means to harvest the hydrogenogenic biomass. The best performance in terms of both H₂ generation potential and process kinetics was observed at pH = 6.5 under all experimental conditions (no inoculum, and untreated or thermally treated inoculum added). H₂ production from food waste was found to be feasible even without inoculum addition, although thermal pre-treatment of the inoculum notably increased the maximum production and reduced the lag phase duration. The analysis of the fermentation products indicated that the biological hydrogen production could be mainly ascribed to a mixed acetate/butyrate-type fermentation. However, the presence of additional metabolites in the digestate, including propionate and ethanol, also indicated that other metabolic pathways were active during the process, reducing substrate conversion into hydrogen. The plateau in H₂ generation was found to mirror the condition at which soluble carbohydrates were depleted. Beyond this condition, homoacetogenesis probably started to play a role in the degradation process.     

Safety assessment of automated vehicles: how to determine whether we have collected enough field data?

Abstract

Objective: The amount of collected field data from naturalistic driving studies is quickly increasing. The data are used for, among others, developing automated driving technologies (such as crash avoidance systems), studying driver interaction with such technologies, and gaining insights into the variety of scenarios in real-world traffic. Because data collection is time consuming and requires high investments and resources, questions like “Do we have enough data?,” “How much more information can we gain when obtaining more data?,” and “How far are we from obtaining completeness?” are highly relevant. In fact, deducing safety claims based on collected data—for example, through testing scenarios based on collected data—requires knowledge about the degree of completeness of the data used. We propose a method for quantifying the completeness of the so-called activities in a data set. This enables us to partly answer the aforementioned questions.

Method: In this article, the (traffic) data are interpreted as a sequence of different so-called scenarios that can be grouped into a finite set of scenario classes. The building blocks of scenarios are the activities. For every activity, there exists a parameterization that encodes all information in the data of each recorded activity. For each type of activity, we estimate a probability density function (pdf) of the associated parameters. Our proposed method quantifies the degree of completeness of a data set using the estimated pdfs.

Results: To illustrate the proposed method, 2 different case studies are presented. First, a case study with an artificial data set, of which the underlying pdfs are known, is carried out to illustrate that the proposed method correctly quantifies the completeness of the activities. Next, a case study with real-world data is performed to quantify the degree of completeness of the acquired data for which the true pdfs are unknown.

Conclusion: The presented case studies illustrate that the proposed method is able to quantify the degree of completeness of a small set of field data and can be used to deduce whether sufficient data have been collected for the purpose of the field study. Future work will focus on applying the proposed method to larger data sets. The proposed method will be used to evaluate the level of completeness of the data collection on Singaporean roads, aimed at defining relevant test cases for the autonomous vehicle road approval procedure that is being developed in Singapore.     

Yttrium recovery from primary and secondary sources: A review of main hydrometallurgical processes

Yttrium is important rare earths (REs) used in numerous fields, mainly in the phosphor powders for low-energy lighting. The uses of these elements, especially for high-tech products are increased in recent years and combined with the scarcity of the resources and the environmental impact of the technologies to extract them from ores make the recycling waste, that contain Y and other RE, a priority.The present review summarized the main hydrometallurgical technologies to extract Y from ores, contaminated solutions, WEEE and generic wastes. Before to discuss the works about the treatment of wastes, the processes to retrieval Y from ores are discussed, since the processes are similar and derived from those already developed for the extraction from primary sources.Particular attention was given to the recovery of Y from WEEE because the recycle of them is important not only for economical point of view, considering its value, but also for environmental impact that this could be generated if not properly disposal.     

Evaluating mortality rates with a novel integrated framework for nonmonogamous species

The conservation of wildlife requires management based on quantitative evidence, and especially for large carnivores, unraveling cause‐specific mortalities and understanding their impact on population dynamics is crucial. Acquiring this knowledge is challenging because it is difficult to obtain robust long‐term data sets on endangered populations and, usually, data are collected through diverse sampling strategies. Integrated population models (IPMs) offer a way to integrate data generated through different processes. However, IPMs are female‐based models that cannot account for mate availability, and this feature limits their applicability to monogamous species only. We extended classical IPMs to a two‐sex framework that allows investigation of population dynamics and quantification of cause‐specific mortality rates in nonmonogamous species. We illustrated our approach by simultaneously modeling different types of data from a reintroduced, unhunted brown bear (Ursus arctos) population living in an area with a dense human population. In a population mainly driven by adult survival, we estimated that on average 11% of cubs and 61% of adults died from human‐related causes. Although the population is currently not at risk, adult survival and thus population dynamics are driven by anthropogenic mortality. Given the recent increase of human‐bear conflicts in the area, removal of individuals for management purposes and through poaching may increase, reversing the positive population growth rate. Our approach can be generalized to other species affected by cause‐specific mortality and will be useful to inform conservation decisions for other nonmonogamous species, such as most large carnivores, for which data are scarce and diverse and thus data integration is highly desirable.     

Characterising the hydrological regime of an ungauged temporary river system: a case study

Temporary streams are characterised by specific hydrological regimes, which influence ecosystem processes, groundwater and surface water interactions, sediment regime, nutrient delivery, water quality and ecological status. This paper presents a methodology to characterise and classify the regime of a temporary river in Southern Italy based on hydrological indicators (HIs) computed with long-term daily flow records. By using a principal component analysis (PCA), a set of non-redundant indices were identified describing the main characteristics of the hydrological regime in the study area. The indicators identified were the annual maximum 30- and 90-day mean (DH4 and DH5), the number of zero flow days (DL6), flow permanence (MF) and the 6-month seasonal predictability of dry periods (SD6). A methodology was also tested to estimate selected HIs in ungauged river reaches. Watershed characteristics such as catchment area, gauging station elevation, mean watershed slope, mean annual rainfall, land use, soil hydraulic conductivity and available water content were derived for each site. Selected indicators were then linked to the catchment characteristics using a regression analysis. Finally, MF and SD6 were used to classify the river reaches on the basis of their degree of intermittency. The methodology presented in this paper constitutes a useful tool for ecologists and water resource managers in the Water Framework Directive implementation process, which requires a characterisation of the hydrological regime and a ‘river type’ classification for all water bodies.     

Using MCDA and GIS for hazardous waste landfill siting considering land scarcity for waste disposal

The main aim of this study was to develop a procedure that minimizes the wasting of space for the siting of hazardous waste landfills as part of a solid waste management system. We wanted to tackle the shortage of land for waste disposal that is a serious and growing problem in most large urban regions. The procedure combines a multi-criteria decision analysis (MCDA) approach with a geographical information system (GIS). The GIS was utilised to obtain an initial screening in order to eliminate unsuitable areas, whereas the MCDA was developed to select the most suitable sites. The novelty of the proposed siting procedure is the introduction of a new screening phase before the macro-siting step aimed at producing a “land use map of potentially suitable areas” for the siting of solid waste facilities which simultaneously takes into consideration all plant types. The issue of obtaining sites evaluations of a specific facility was coupled with the issue of not wasting land appropriate to facilitate other types of waste management options. In the developed case study, the use of an innovative criteria weighting tool (the “Priority Scale”) in combination with the Analytic Hierarchy Process was useful to easier define the priorities of the evaluation criteria in comparison with other classic methods such as the Paired Comparison Technique in combination with the Simple Additive Weighting method.