Analysis of polycyclic aromatic hydrocarbons (PAHs) in airborne particles by direct sample introduction thermal desorption GC/MS

The technique of thermal desorption (TD)–GC/MS was evaluated for measuring airborne, 4–6 ring polycyclic aromatic hydrocarbons (PAHs) collected onto quartz filters. TD provides a more readily automated and sensitive alternative to traditional solvent extraction, decreasing the time/cost of analysis and reducing the risk of analyte loss or sample contamination. The developed method was successfully applied to the analysis of PAH standard solutions loaded on sorbent tubes packed with quartz wool and the graphitized carbon black sorbent Carbograph2. The optimized method showed high desorption efficiency over the whole range of target PAHs with good precision, linearity and sensitivity. The proposed method was verified on an urban dust Standard Reference Material (SRM 1649a); the experimentally determined concentrations agreed with the certified ranges (95% confidence limit) for all target compounds except benzo[a]anthracene, which fell just outside the narrow certified range. The desorption efficiency and the reproducibility of the method was evaluated by analysing pieces of real sample filters sampled from urban air for a period of 24 h. The results confirmed the homogeneity of the filter and showed high recovery efficiencies for all target PAHs.     

Effects of calcium hydroxide and calcium chloride addition to bentonite in iron ore pelletization.

Pyrite ash is created as waste from the roasting of pyrite ores during the production of sulphuric acid. These processes generate great amounts of pyrite ash waste that is generally land filled. This creates serious environmental pollution due to the release of acids and toxic substances. Pyrite ash waste can be utilized in the iron production industry as a blast furnace feed to process this waste and prevent environmental pollution. The essential parameters affecting the pelletization process of pyrite ash were studied using bentonite as a binder. Experiments were then carried out using bentonite and a mixture of bentonite with calcium hydroxide and calcium chloride in order to make the bentonite more effective. The metallurgical properties of pyrite ash, bentonite, calcium hydroxide, calcium chloride, a mixture of these and sintered pellets were studied using X-ray analysis. The crushing strength tests were carried out to investigate the strength of pyrite ash waste pellets. The results of these analyses showed that pyrite ash can be agglomerated to pellets and used in the iron production industry as a blast furnace feed. The crushing strength of the pellets containing calcium hydroxide and calcium chloride in addition to bentonite was better than the strength of pellets prepared using only bentonite binder.     

Numerical analysis of the anaerobic co-digestion of the organic fraction from municipal solid waste and wastewater: prediction of the possible performances at Olmeto plant in Perugia (Italy).

Anaerobic digestion is mainly used for sewage sludge stabilization and for treatment of waste that has a high organic content. It also represents a powerful method for obtaining energy by means of natural gas production. Co-digestion particularly combines different organic substrates to generate a homogeneous mixture as input to the anaerobic reactor in order to increase process performance. Reactions kinetics and knowledge of process analysis represent the keys for good planning and correct management. In this paper a model to simulate the main reactions involved in anaerobic co-digestion is presented. The model was created to analyse the possible performance of the treatment plant in Olmeto, Marsciano (Perugia) in Italy. The plant is still in an experimental phase with regard to the co-digestion process and numerical simulations represent a useful tool during development of the correct management procedures for the operational phase and a good methodoly for addressing further pilot plant experiments.     

Working backwards to move forwards: Graph-based connectivity metrics for reserve network selection

In this paper we apply graph theory in a reserve selection exercise to explore the tradeoffs between maintaining connectivity and minimizing the total area of a protected area network. Rather than focus on a single organism, we used a multi-species approach and looked at the tradeoff curves for organisms with varying dispersal abilities. We first generated the tradeoff curves using a graph-based metric to determine the importance of individual patches for maintaining connectivity. We then performed an analogous set of analyses using patch size as a surrogate measure of importance.     

A modular approach to Integrated Assessment modeling

In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability.     

Seasonal variations in nickel and vanadium in Mont Blanc snow and ice dated from the 1960s and 1990s

Ni and V have been determined in snow and ice collected at a high altitude location (Col du D?me) near the summit of Mont Blanc on the French-Italian border; dated from the 1960s and 1990s. Ni and V were simultaneously determined by inductively coupled plasma sector field mass spectrometry. Measured concentrations range from 6 to 700 pg g(-1) and 4 to 1,100 pg g(-1) for Ni and V, respectively. The results show pronounced seasonal variations in the concentrations of both metals, with high concentration values in summer layers and much lower values for winter layers. These seasonal variations are linked especially with the existence of inversion layers during winter months. Ni and V concentrations in excess of the contributions from rock and soil dust (Ni(excess), V(excess)) appear to be mainly associated with anthropogenic inputs, with pronounced seasonal variations. Large variations in the V(excess)/Ni(excess) ratio are observed, with a higher ratio in summer than in winter. This shows differences in anthropogenic inputs at Col du D?me during the different parts of the year. The above ratio was compared with the corresponding ratios for oil combustion from stationary sources and the exhaust from gasoline and diesel engines. It appears that Ni and V concentrations at Col du D?me are probably the result of changing combinations of contributions from oil combustion for power generation, industrial and residential uses, on one side, and automobile and truck traffic, on the other side, with possibly a significant contribution from Ni smelters in Russia during winter months.     

Optimizing the removal of small fish passage barriers

Removing small artificial barriers that hinder upstream migrations of fish is a major problem in riparian habitat restoration. Because of budgetary limitations, it is necessary to prioritize barrier removal and repair decisions. These have usually been based on scoring and ranking procedures, which, although simple to use, can be very inefficient in terms of increasing the amount of accessible instream habitat. We develop a novel decision-making approach, based on integer programming techniques, which optimizes repair and removal decisions. Results show based on real datasets of barrier culverts located in Washington State that scoring and ranking is over 25% below the optimum on average and a full 100% below in the worst case, producing no net habitat gain whatsoever. This is compared to a dynamic programming method that was able to find optimal solutions in less than a second, even for problems with up to several hundred variables, and a heuristic method, which found solutions with less than a 1% average optimality gap in even less time.