Assessing the economics of pre-fragmentation material recovery within the UK

The 2006 end-of-life vehicles (ELVs) directive target for the recycled and reused material content of an ELV has been undertaken using the current recovery infrastructure within the UK. The current expectation is that the conformance for the 2006 recycling target will be mainly achieved using existing post-fragmentation separation technologies rather than manually disassembling vehicles into their constituent materials. With the economic pressure of the current legislative targets weighing heavily on end-of-life stakeholders, and the further increase of recycling levels for 2015, it is important to understand “when” and “if” manual dismantling activities become economically viable within a dramatically changing vehicle recovery industry. This paper describes a method of costing the dismantling of specific makes and models of vehicle due for retirement in 2015, and discusses the economic implications of such practice and possible strategic directions for pre-fragmentation vehicle recovery.     

Comparison of different static methods for assessment of AMD generation potential in mining waste dumps in the Muteh Gold Mines,Iran

Acid mine drainage (AMD) gives rise to several problems in sulfide-bearing mineral deposits whether in an ore body or in the mining wastes and tailings. Hence, several methods and parameters have been proposed to evaluate the acid-producing and acid-neutralizing potential of a material. This research compares common static methods for evaluation of acid-production potential of mining wastes in the Muteh gold mines by using 62 samples taken from six waste dumps around Senjedeh and Chah-Khatoun mines. According to a detailed mineralogical study, the waste materials are composed of mica-schist and quartz veins with a high amount of pyrite and are supposed to be susceptible to acid production, and upon a rainfall, they release acid drainage. All parameters introduced in different methods were calculated and compared in this research in order to predict the acid-generating and neutralization potential, including APP, NNP, MPA, NPR, and NAGpH. Based on the analytical results and calculation of different parameters, all methods are in a general consensus that DWS-02 and DWS-03 waste dumps are acid-forming which is clearly attributed to high content of pyrite in samples. DWS-04 is considered as non-acid forming in all methods except method 8 which is uncertain about its acid-forming potential and method 7 which considers a low potential for it. DWC-01 is acid-forming based on all methods except 8, 9, 10, and 11 which are also uncertain about its potential. The methods used are not reached to a compromise on DWS-01 and DWC-02 waste dumps. It is supposed that method 7 gives the conservationist results in all cases. Method 8 is unable to decide on some cases. It is recommended to use and rely on results provided by methods 1, 2, 3, and 12 for taking decisions for further studies. Therefore, according to the static tests used, the aforementioned criteria in selected methods can be used with much confidence as a rule of thumb estimation.     

A Robust Optimization Model for an Invasive Species Management Problem

Invasive species pose a significant threat to global biodiversity. Managing invasive species often involves modeling the species’ spread pattern, estimating control costs and damage costs due to the invasion, designing control efforts, and accounting for uncertainties in model parameters. Dealing with uncertainty is arguably the most important part of the process, since biological, environmental, and economic factors can cause parameter values to vary greatly. Managers need decision tools that are robust to such limited or variable information. Here, we present a robust spatial optimization model to select treatment sites in a way that maximally reduces the size of an invasive population, given a constraint on financial resources. We develop an integer programming model that includes population dynamics and management costs over space and time. The model incorporates uncertainty in the available budget and the invasive spread rate as sets of discrete scenarios to determine a robust, cost-effective management plan in a novel way.     

The effectiveness of digital soil mapping to predict soil properties over low-relief areas

This study investigates the ability of different digital soil mapping (DSM) approaches to predict some of physical and chemical topsoil properties in the Shahrekord plain of Chaharmahal-Va-Bakhtiari province, Iran. According to a semi-detailed soil survey, 120 soil samples were collected from 0 to 30 cm depth with approximate distance of 750 m. Particle size distribution, coarse fragments (CFs), electrical conductivity (EC), pH, organic carbon (OC), and calcium carbonate equivalent (CCE) were determined. Four machine learning techniques, namely, artificial neural networks (ANNs), boosted regression tree (BRT), generalized linear model (GLM), and multiple linear regression (MLR), were used to identify the relationship between soil properties and auxiliary information (terrain attributes, remote sensing indices, geology map, existing soil map, and geomorphology map). Root-mean-square error (RMSE) and mean error (ME) were considered to determine the performance of the models. Among the studied models, GLM showed the highest performance to predict pH, EC, clay, silt, sand, and CCE, whereas the best model is not necessarily able to make accurate estimation. According to RMSE%, DSM has a good efficiency to predict soil properties with low and moderate variabilities. Terrain attributes were the main predictors among different studied auxiliary information. The accuracy of the estimations with more observations is recommended to give a better understanding about the performance of DSM approach over low-relief areas.     

Concentrations of polybrominated diphenyl ethers, organochlorine compounds and nitro musks in mother's milk from Germany (Bavaria)

The aim of this study was to determine a new spectrum of substances that will be selected for future breast milk monitoring in Bavaria, Germany. Up to now, the analysis of breast milk in Bavaria was limited to selected organochlorine pesticides (OCP) and polychlorinated biphenyls (PCB). Information on background levels of toxicologically interesting substances, such as dioxins and dioxin-like polychlorinated biphenyls (dl-PCB) or on flame retardants, such as polybrominated diphenyl ethers (PBDE) are very limited or not available for Bavaria. We present here levels on OCP, some nitro musks, indicator PCB, polychlorinated dibenzo-p-dioxins (PCDD), polychlorinated dibenzofurans (PCDF) and dl-PCB concentrations in breast milk collected at 12 weeks post-partum of 43 primiparous mothers living in Bavaria. The average concentrations of PCDD, PCDF and dl-PCB were 4.98, 4.93 and 9.92 pg WHO-TEQ g(-1) lipid, respectively. The mean contribution of PCDD, PCDF, non-ortho and mono-ortho PCB to the total WHO-TEQ is consistently about 25% each. Furthermore the concentration on PBDE in breast milk at two sampling points, 12 weeks and 16 weeks after delivery, were determined. Overall, 19 PBDE congeners were analysed, however the level of 12 PBDE congeners were below the limit of detection. BDE-153 and BDE-47 were the predominant congeners accounting for about 66% of the total PBDE. The means of the total concentrations of PBDE (five congeners) at the first and second sampling point were 1.90 and 2.03 ng g(-1) lipid, respectively. Based on our results the overall concentrations of the analysed substances in milk samples from Bavaria are consistent with the levels of breast milk samples of other European countries reflecting the low background body burden of these compounds.     

Determining the most suitable areas for artificial groundwater recharge via an integrated PROMETHEE II-AHP method in GIS environment (case study: Garabaygan Basin, Iran)

Flood spreading is a suitable strategy for controlling and benefiting from floods. Selecting suitable areas for flood spreading and directing the floodwater into permeable formations are amongst the most effective strategies in flood spreading projects. Having combined geographic information systems (GIS) and multi-criteria decision analysis approaches, the present study sought to locate the most suitable areas for flood spreading operation in the Garabaygan Basin of Iran. To this end, the data layers relating to the eight effective factors were prepared in GIS environment. This stage was followed by elimination of the exclusionary areas for flood spreading while determining the potentially suitable ones. Having closely examined the potentially suitable areas using the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) II and analytic hierarchy process (AHP) methods, the land suitability map for flood spreading was produced. The PROMETHEE II and AHP were used for ranking all the alternatives and weighting the criteria involved, respectively. The results of the study showed that most suitable areas for the artificial groundwater recharge are located in Quaternary Q_g and Q^gsc geologic units and in geomorphological units of pediment and Alluvial fans with slopes not exceeding 3 %. Furthermore, significant correspondence between the produced map and the control areas, where the flood spreading projects were successfully performed, provided further evidence for the acceptable efficiency of the integrated PROMETHEE II-AHP method in locating suitable flood spreading areas.