Abstract: Traditionally, fast screening for the presence of cocaine in unknown powders is performed by means of colour tests. The major drawbacks of these tests are subjective colour evaluation depending on the operator (50 shades of blue) and a lack of selectivity. An alternative fast screening technique is Fourier Transform InfraRed (FTIR) spectrometry. This technique provides spectra that are difficult to interpret without specialized expertise and showing a lack of sensitivity for the detection of cocaine in mixtures. To overcome these limitations, a portable FTIR spectrometer using Attenuated Total Reflectance (ATR) sampling was combined with a multivariate technique, called Support Vector Machines (SVM). Representative street drug powders (n = 482), seized during the period January 2013 to July 2015, and reference powders (n = 33) were used to build and validate a classification model (n = 515) and a quantification model (n = 378). Both models were compared with the conventional chromatographic techniques. The SVM classification model showed a high sensitivity, specificity and efficiency (99%). The SVM quantification model determined cocaine content with a root mean squared error of prediction (RMSEP) of 6% calculated over a wide working range from 4 to 99 w%. In conclusion, the developed models resulted in a clear output (cocaine detected or cocaine not detected) and a reliable estimation of the cocaine content in a wide variety of mixtures. The ATR-FTIR technique combined with SVM is a straightforward, user-friendly and fast approach for routine classification and quantification of cocaine in seized powders.

Abstract: Photocatalysis assisted oxidation of carbon black was performed using TiO2 photocatalyst under UV illumination in an atmosphere with NO, O-2 and water vapor at 150 degrees C. Carbon is oxidized mainly to CO2 while NO is selectively converted to N-2. Enhanced O-2 and NO concentrations have a positive effect on the carbon oxidation rate. At a concentration of 3000 ppm NO and 13.3% O-2 in the gas phase the carbon oxidation rate reaches 2.3 mu g(carbon)/mg(TiO2) h, at a formal electron/photon quantum efficiency of 0.019. HR SEM images reveal uniform gradual reduction of the carbon particle size irrespective of the distance to TiO2 photocatalyst particles in the presence of NO, O-2 and H2O. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: This study focuses on four textile industries (DH-GEDA, NOYA, ALMHADI, and ALSAR) established between 2005 and 2008 in the peri-urban areas of Dukem and Gelan. The objectives of the study were to generate baseline information regarding the concentration levels of selected pollutants and to analyze their effects on biophysical environments. This study also attempts to explore the level of exposure that humans and livestock have to polluted effluents and the effects thereof. The findings of this study are based on data empirically collected from two sources: laboratory analysis of sample effluents from the four selected textile plants and quantitative as well as qualitative socioeconomic data collection. As part of the latter, a household survey and focus group discussions (FGDs) with elderly and other focal persons were employed in the towns of Dukem and Gelan. The results of the study show that large concentrations of biological oxygen demand (BOD5), chemical oxygen demand (COD), total suspended solids (TSS), and pH were found in all the observed textile industries, at levels beyond the permissible discharge limit set by the national Environmental Protection Authority (EPA). Furthermore, sulfide (S2), R-phosphate (R-PO43), and Zn were found in large concentrations in DH-GEDA and ALMHADI, while high concentrations were also identified in samples taken from ALSAR and ALMHADI. In spite of the clear-cut legal tools, this study shows that the local environment, people, and their livestock are exposed to highly contaminated effluents. We therefore recommend that the respective federal and regional government bodies should reexamine the compliance to and actual implementation of the existing legal procedures and regulations and respond appropriately.

Abstract: Smart grids (SGs) have a central role in the development of the global power sector. Cost-benefit analyses and environmental impact assessments are used to support policy on the deployment of SG systems and technologies. However, the conflicting and widely varying estimates of costs, benefits, greenhouse gas (GHG) emission reduction, and energy savings in literature leave policy makers struggling with how to advise regarding SG deployment. Identifying the causes for the wide variation of individual estimates in the literature is crucial if evaluations are to be used in decision-making. This paper (i) summarizes and compares the methodologies used for economic and environmental evaluation of SGs (ii) identifies the sources of variation in estimates across studies, and (iii) point to gap in research on economic and environmental analyses of SG systems. Seventeen studies (nine articles and eight reports published between 2000 and 2015) addressing the economic costs versus benefits, energy efficiency, and GHG emissions of SGs were systematically searched, located, selected, and reviewed. Their methods and data were subsequently extracted and analysed. The results show that no standardized method currently exists for assessing the economic and environmental impacts of SG systems. The costs varied between 0.03 and 1143 M/yr, while the benefits ranged from 0.04 to 804 M/yr, suggesting that SG systems do not result in cost savings The primary energy savings ranged from 0.03 to 0.95 MJ/kWh, whereas the GHG emission reduction ranged from 10 to 180 gCO2/kWh, depending on the country grid mix and the system boundary of the SG system considered. The findings demonstrate that although SG systems are energy efficient and reduce GHG emissions, investments in SG systems may not yield any benefits. Standardizing some methodologies and assumptions such as discount rates, time horizon and scrutinizing some key input data will result in more consistent estimates of costs and benefits, GHG emission reduction, and energy savings.

Abstract: We estimate a hedonic-pricing model using geo-coded farmland-transaction data from the Campine region, situated in the north-east of Belgium. Unlike previous hedonic studies, we use the method of unconditional quantile regression (Firpo et al., in Econometrica 77(3):953973, 2009). An important advantage of this new method over the traditional conditional quantile regression (Koenker and Bassett, in Econometrica 46(1):3350, 1978) is that it allows for the estimation of potentially heterogeneous effects of cadmium pollution along the entire (unconditional) distribution of farmland prices. Using a threshold specification of the hedonic-pricing model, we find evidence of a U-shaped valuation pattern, where cadmium pollution of the soil has a negative and significant impact on prices only in the middle range of the distribution, insofar as cadmium concentrations are above the regulatory standard of 2 parts per million for agricultural land. Results obtained from a probit model to classify land plots into different price segments further suggest that the heterogeneous impact of soil pollution on price can be directly related to the variety of amenities that farmland provides.

Abstract: Current cross-sectional methodologies measuring climate change impacts assume that regions at the same latitude face a similar climate response and therefore have the same adaptive capacity. This paper proves that assumption to be erroneous in the European Union. It does so by ameliorating the Ricardian methodology by restricting which farmers (and therefore which adaptation options) are allowed in the dataset. In doing so, a comparative Ricardian methodology is suggested that makes it possible to examine, for the first time, how the climate responsiveness of a region changes if adaptive capacity changes. The paper combines climate, soil, geographic, socio-economic, and farm-level data in a linear mixed-effect model and examines whether Eastern and Western Europe have the same climate responses and how these responses change if regional adaptive capacity increases. The paper concludes that both regions currently have a significantly different climate response, but that if Eastern Europe were to implement the same adaptation options as Western Europe, it could avoid a large decrease in land value and even benefit from climate change depending on the climate scenario.

Abstract: The increasing production of nitrogen-containing fertilizers is crucial to meet the global food demand, yet high losses of reactive nitrogen associated with the food production/consumption chain progressively deteriorate the natural environment. Currently, mesophilic nitrogen-removing microbes eliminate nitrogen from wastewaters. Although thermophilic nitrifiers have been separately enriched from natural environments, no bioreactors are described that couple these processes for the treatment of nitrogen in hot wastewaters. Samples from composting facilities were used as inoculum for the batch-wise enrichment of thermophilic nitrifiers (350 days). Subsequently, the enrichments were transferred to a bioreactor to obtain a stable, high-rate nitrifying process (560 days). The community contained up to 17% ammonia-oxidizing archaea (AOAs) closely related to 'Candidatus Nitrososphaera gargensis', and 25% nitrite-oxidizing bacteria (NOBs) related to Nitrospira calida. Incorporation of C-13-derived bicarbonate into the respective characteristic membrane lipids during nitrification supported their activity as autotrophs. Specific activities up to 198 +/- 10 and 894 +/- 81 mg N g(-1) VSS per day for AOAs and NOBs were measured, where NOBs were 33% more sensitive to free ammonia. The NOBs were extremely sensitive to free nitrous acid, whereas the AOAs could only be inhibited by high nitrite concentrations, independent of the free nitrous acid concentration. The observed difference in product/substrate inhibition could facilitate the development of NOB inhibition strategies to achieve more cost-effective processes such as deammonification. This study describes the enrichment of autotrophic thermophilic nitrifiers from a nutrient-rich environment and the successful operation of a thermophilic nitrifying bioreactor for the first time, facilitating opportunities for thermophilic nitrogen removal biotechnology.

Abstract: Jackson Pollock's Number 1A, 1948 painting was investigated using in situ scanning macro-x-ray fluorescence mapping (MA-XRF) to help characterize the artist's materials and his creative process. A multivariate curve resolution-alternating least squares (MCR-ALS) approach was used to examine the hyperspectral data and obtain distribution maps and signature spectra for the paints he used. The composition of the paints was elucidated based on the chemical elements identified in the signature spectra and a tentative list of pigments, fillers and other additives is proposed for eleven different paints and for the canvas. The paint distribution maps were used to virtually reconstruct the artist process and document the sequence and manner in which Pollock applied the different paints, using deliberate and specific gestures.

Abstract: The conventional treatment of municipal wastewater by means of activated sludge is typically energy demanding. Here, the potential benefits of: (1) the optimization of mesophilic digestion; and (2) transitioning to thermophilic sludge digestion in three wastewater treatment plants (Tilburg-Noord, Land van Cuijk and Bath) in the Netherlands is evaluated, including a full-scale trial validation in Bath. In Tilburg-Noord, thermophilic sludge digestion covered the energy requirements of the plant (102%), whereas 111% of sludge operational treatment costs could be covered in Bath. Thermophilic sludge digestion also resulted in a strong increase in nutrient release. The potential for nutrient recovery was evaluated via: (1) stripping/absorption of ammonium; (2) autotrophic removal of ammonium via partial nitritation/anammox; and (3) struvite precipitation. This research shows that optimization of sludge digestion may lead to a strong increase in energy recovery, sludge treatment costs reduction, and the potential for advanced nutrient management in full-scale sewage treatment plants. (C) 2016 Elsevier Ltd. All rights reserved.

Abstract: Both landfill taxes and Enhanced Waste Management (EWM) practices can mitigate the scarcity issue of landfill capacity by respectively reducing landfilled waste volumes and valorising future waste streams. However, high landfill taxes might erode incentives for EWM, even though EWM creates value by valorising waste. Concentrating on Flanders (Belgium), the paper applies dynamic optimisation modelling techniques to analyse how landfill taxation and EWM can reinforce each other and how taxation schemes can be adjusted in order to foster sustainable and welfare maximising ways of processing future waste streams. Based on the Flemish simulation results, insights are offered that are generally applicable in international waste and resource management policy. As shown, the optimal Flemish landfill tax that optimises welfare in the no EWM scenario is higher than the one in the EWM scenario (93 against (sic)50/ton). This difference should create incentives for applying EWM and is driven by the positive external effects that are generated by EWM practices. In Flanders, as the current landfill tax is slightly lower than these optimal levels, the choice that can be made is to further increase taxation levels or show complete commitment to EWM. A first generally applicable insight that was found points to the fact that it is not necessarily the case that the higher the landfill tax, the more effective waste management improvements can be realised. Other insights are about providing sufficient incentives for applying EMW practices and formulating appropriate pleas in support of technological development. By these insights, this paper should provide relevant information that can assist in triggering the transition towards a resource efficient, circular economy in Europe. (C) 2016 Elsevier Ltd. All rights reserved.

Abstract: Iran's energy system is extremely dependent on fossil fuels which, in turn, have led to problems such as fossil fuels depletion, social, economic and environmental damage and territorial imbalance. The country should therefore design a sustainable energy system based on clean energy as well as renewable energy. Accordingly, and given that Iran's rural areas suffer from the unsustainable energy system, it is necessary to integrate renewable energy into comprehensive development programs in general, and into rural development programs, specifically. This review paper answers the following questions: Why is renewable energy important for Iran at national and rural levels? How is renewable energy related to sustainable rural development? and What are the challenges in the promotion of renewable energy technologies in Iran? The paper concludes that although renewable energy has potential for development in Iran's rural areas due to environmental, social and economic advantages, it could face some infrastructural, managerial, socio-cultural and economic challenges. Accordingly, aggressive and innovative policy making is required to meet these challenges. (C) 2016 Elsevier Ltd. All rights reserved.

Abstract: A major objective of European agricultural policy is to have a sustainable and efficient farming sector that is applying environmentally-friendly production methods. Policy makers aim to combine a strong economic performance and a sustainable use of natural resources. Therefore, it is important to measure and to assess farm sustainability. For a large dataset of Flemish dairy farms, a valuation method that is based on the concept of opportunity costs is used to calculate and analyze differences among the sample farms with respect to the creation of sustainable value. But more important than measuring the creation of sustainable value is to analyze differences in sustainable efficiency. Therefore, sustainable efficiency measures are calculated and differences in sustainable efficiency are explained. Using panel data, an effect model captures the determinants of sustainable efficiency of the studied farms. The empirical model shows that, in general, larger farms have a higher sustainable efficiency. Also farmer's age and dependency on support payments proved to be determining characteristics for observed differences in sustainable efficiency.

Abstract: Indicator-based monitoring tools are frequently applied for sustainability assessments, also in agriculture. However, many indicators focus on a rather restricted number of sustainability aspects such as economy or ecology. Moreover the choice of the indicator is rarely explained. The aim of our study was to develop an indicator-based monitoring tool for integrated farm sustainability – i.e. taking into account economic and ecological and social aspects – based on a supported vision of sustainable agriculture and using a set of relevant indicators. Hereby, specific attention was paid to aspects of communication and user-friendliness. Four methodological steps were considered: (i) translating the major principles of a supported vision of sustainable Flemish agriculture into concrete and relevant themes; (ii) designing indicators to monitor progress towards sustainability for each of those themes; (iii) aggregating the indicators into an integrated farm sustainability monitoring tool and (iv) applying the monitoring tool on a practical farm, as a first attempt at end-use validation. Stakeholder participation and expert consulting played an important part in each of these methodological steps. As a case study, the methodology was applied to Flemish dairy farms. As a result, we developed MOTIFS, a user-friendly and strongly communicative indicator-based monitoring tool that allows the measurement of progress towards integrated sustainable dairy farming systems and fits within a well-founded methodological framework. MOTIFS is based on the equality of the economic, ecological and social sustainability dimensions, and this equality is inherently built into the system. Through the applied methodology, we founded the selected themes and indicators and we avoided using indicators that are not relevant to the problem at hand.

Abstract: This paper uses a mechanistic frontier approach as a reference to evaluate the ability of conventional parametric (SFA) and non-parametric (DEA) frontier approaches for analyzing economicenvironmental trade-offs. Conventional frontier approaches are environmentally adjusted through incorporating the materials balance principle. The analysis is worked out for the Flemish pig finishing case, which is both representative and didactic. Results show that, on average, SFA and DEA yield adequate economicenvironmental trade-offs. Both methods are good estimators for technical efficiency. Cost allocative and environmental allocative efficiency scores are less robust, due to the well-known methodological advantages and disadvantages of SFA and DEA. For particular firms, SFA, DEA and the mechanistic approach may yield different economicenvironmental trade-offs. One has therefore to be careful when using conventional frontier approaches for firm-specific decision support. The mechanistic approach allows for optimizing performances per average present finisher, which is the production unit in pig finishing. Conventional frontier methods do not allow for this optimization since the number of average present finishers varies along the production functions. Since the mechanistic production function is based on underlying growth, feed uptake and mortality functions, additional firm-specific indicators can also be calculated at each point of the production function.

Abstract: This research uses multi-objective optimisation to determine the optimal mixture of energy and transportation technologies, while optimising economic and environmental impacts. We demonstrate the added value of using multi-objective mixed integer linear programming (MOMILP) considering economies of scale versus using continuous multi-objective linear programming assuming average cost intervals. This paper uses an improved version to solve MOMILPs exactly. To differentiate optimal solutions with and without subsidies, the impact of policy on the Pareto frontier is assessed. We distinguish between minimising economic life cycle costs (complete rationality) and required investments (bounded rationality). The approach is illustrated using a Belgian company with demands for electricity and transport. Electricity technologies are solar photovoltaics and the grid; transportation includes internal combustion engine vehicles, grid powered battery electric vehicles (BEVs), and solar-powered BEVs. The impact of grid powered BEVs to reduce GHG emissions is limited, yet they are less costly than solar panels to decrease emissions. Current policy measures are found to be properly targeting rational investors who consider life cycle costs, while private (potentially bounded rational) investors often focus on required investments only.