Using non-equilibrium biosorption column modelling for improved process efficiency

An unsteady-state biosorption column model in one space variable is considered in this paper. The theoretical study is motivated by the need for predicting the dependent variables of biosorption columns for removal of heavy metals from wastewater, which is potentially an important technology in cleaner production. Pollutant concentrations in the bulk phase, in the liquid filling the pores and in the solid biomass along the axial coordinate of the column were evaluated for a wide range of physical and chemical parameters of the global process. In particular, the assumption of instantaneous chemical reactions is replaced by a more realistic expression taking into account chemical kinetics and fluid advection time scales separately. The resulting system of partial differential equations was solved by means of a reliable numerical algorithm based on the method of lines. The data obtained using the model described in this paper are compared with published experimental data and an estimation of the increased efficiency is made.     

Yield response of potato to spatially patterned nitrogen application

Although crop response to nitrogen fertilization has long been studied, classical experimental designs have led to inadequate accounting of spatial variability in field properties and yield response. Analytical methods to explicitly account for spatial variability now exist but the complementary modification of experimental design is still developing. There is a need to combine these analytical methods with non-traditional experimental design. A 2-year study was implemented to assess the response of potato (Solanum tuberosum cv. Kennebec) yield to nitrogen fertilizer rate. We used a transect-type plot design where four nitrogen treatments (0, 56, 112, and 280 kg N ha^?1) were applied systematically in a continuous sinusoidal pattern along longitudinal transects. Measured field properties included topography, soil texture, pre-application soil nitrate levels, and plant available soil water content. A random field linear model was used to simultaneously account for treatment effects and soil properties. The results showed that treatment effects were significantly different from each other; however, if spatially correlated errors were accounted for, these differences were smaller and significance levels lower. Nitrogen response functions varied widely throughout the field. Of the covariates, only clay content proved important in explaining spatial differences in response to N. The sinusoidal response pattern of N was similar over the 2 years but the amplitudes varied due to differences in weather. Interactions between uncharacteristically high rainfall and a sandy field soil may have minimized discernable effects of the other covariates. The results demonstrated how the statistical analysis of potato response to a patterned application of nitrogen fertilizer can take advantage of spatial correlations to understand the response of potato to nitrogen application over larger areas.     

Building resilience to climate change – the role of cooperation in alpine tourism networks

While there is ample – though partially contradictory – evidence regarding the effects climate change will have on various regions of the world, there is only very limited work dedicated to the analysis of different governance structures, and how these structures are likely to influence the resilience of alpine tourism systems in the face of climate change. We present an analytical framework based on network theory, and apply this to the Swiss case study destination of Engelberg, in order to deduct a number of insights for the future assessment of resilience based on the cooperation of local actors. The main aim of the paper is to come up with comparable resilience metrics based on social network analysis in order to assess the structural strengths and weaknesses of a geographically delimited tourism system in the face of climate change. Together with the action potential of the individual actors these structural properties influence the adaptive capacity of both individual actors, and the tourism system as a whole. In line with comparable studies, we identify structural strengths and weaknesses around the core-periphery distribution (centrality), subgroups (modularity) and information flows (path length). We find that the Engelberg network follows an almost ideal-typical scale-free structure and the overall cooperation rate (density) is comparable to other tourism networks. The main weaknesses of the network with regard to climate change resilience are the lacking integration of public sector actors and the relatively high number of actors in the periphery of the network.     

Climate change impact on the olive pollen season in Mediterranean areas of Italy: air quality in late spring from an allergenic point of view

Recent studies have shown that there are many effects of climate change on aeroallergens, and thus on allergic diseases in humans. In the Mediterranean region, despite the importance of the olive tree for production, there is high allergenicity of olive pollen and related risks to human health. Aerobiological sampling techniques can be used to analyse the pollinosis phenomenon through determination of mean daily pollen concentrations per cubic metre of air. The present study was carried out from 1999 to 2008 in 16 olive-growing areas in Italy, to update the information on the pollinosis characteristics of Olea europaea in the study areas. The analysis of the average flowering season over the study period highlights a temporal scaling of pollen in the atmosphere that depends on the different climatic characteristics. This is mainly dependent on temperature, and in part, determined by latitude. Generally, the levels of O. europaea pollen in the atmosphere are higher from mid-April to the end of June, with the period of greatest risk to human health due to this olive pollen in this area currently limited primarily to the last 10 days of May. However, the pollen season can move, depending on the climate scenario considered, and data here can be used to determine potential time shifts in pollinosis that might cause more precocious asthma and allergy problems. The allergy season for this type of pollen might be significantly precocious in future decades (20–30 days earlier in the year), which will impact on the severity and duration of allergies attributable to olive tree pollen.