Pollutant concentration profile reconstruction using digital soft sensors for biodegradation and exposure assessment in the presence of model uncertainty

A new approach to the problem of environmental hazard assessment and monitoring for pollutant biodegradation reaction systems in the presence of uncertainty is proposed using soft sensor-based pollutant concentration dynamic profile reconstruction techniques. In particular, a robust reduced-order soft sensor is proposed that can be digitally implemented in the presence of inherent complexity and the inevitable model uncertainty. The proposed method explicitly incorporates all the available information associated with a process model characterized by varying degrees of uncertainty, as well as available sensor measurements of certain physicochemical quantities. Based on the above information, a reduced-order soft sensor is designed enabling the reliable reconstruction of pollutant concentration profiles in complex biodegradation systems that can not be always achieved due to physical and/or technical limitations associated with current sensor technology. The option of using the aforementioned approach to compute toxic load and persistence indexes on the basis of the reconstructed concentration profiles is also pursued. Finally, the performance of the proposed method is evaluated in two illustrative environmental hazard assessment case studies.     

Characterization of atmospheric particulates, particle-bound transition metals and polycyclic aromatic hydrocarbons of urban air in the centre of Athens (Greece)

The concentrations of trace metals and polycyclic aromatic hydrocarbons (PAHs) adsorbed to total suspended particulate (TSP) and finer fractions of airborne particulate matter (PM) were determined from a site in the centre of Athens (Greece), which is characterized by heavy local traffic and is densely populated, during the winter and summer periods in 2003-2004. Also, we collected and analyzed samples of diesel and gasoline exhaust particles from local vehicles (buses, taxis and private cars) and from chimney exhaust of residential central heating appliances. A seasonal effect was observed for the size distribution of aerosol mass, with a shift to larger fine fractions in winter. The most commonly detected trace metals in the TSP and PM fractions were Fe, Pb, Zn, Cu, Cr, V, Ni and Cd and their concentrations were similar to levels observed in heavily polluted urban areas from local traffic and other anthropogenic emissions. Analysis of 16 PAHs bound to PM showed that they are mostly traffic related. In general, the fine particulate PAHs concentrations were higher than coarse particles. The most common PAHs in PM(10.2) and PM(2.1) were pyrene, phenanthrene, acenapthylene and fluoranthene, which are associated with diesel and gasoline exhaust particles. The results of this study underlined the importance of local emission sources, especially vehicular traffic, central heating and other local anthropogenic emissions. Compared with other big cities, Athens has much higher levels of airborne particles, especially of the finer fractions PM(10) and PM(2.5), correlated with traffic-related air pollution.     

Optimizing safety-constrained solvent selection for process systems with economic uncertainties

Solvents are very commonly used in industrial facilities for a multitude of reasons. Traditionally, solvent selection has been based on minimizing the process operating cost while satisfying a set of operational requirements. Regrettably, safety considerations have typically been overlooked during the design phase. In this paper, a systematic approach is introduced to integrate safety issues into solvent selection and provides a computationally effective method for establishing tradeoffs between the economic and safety objectives. In order to quantify the risk associated with the solvent, we focus on the potential spillage of the solvent and introduce a risk index that is a function of the amount of solvent used and stored, as well as the Permissible Exposure Limit (PEL) dictated by regulatory directives. An optimization formulation is developed and the associated mathematical program solved to select optimal solvents and blends while incorporating economic, technical, and safety considerations. Tradeoff (Pareto) curves are developed to represent the multi-objective optimization results and tradeoffs. Furthermore, economic-data uncertainty and variability over expected ranges are included in the optimization formulation to conduct an insightful sensitivity analysis. Finally, an illustrative case study is considered via increasing levels of complexity in order to evaluate the proposed optimization method which considers both operating cost and safety risk implications in the presence of economic uncertainties.     

Database-driven models of the world's Large Marine Ecosystems

We present a new methodology for database-driven ecosystem model generation and apply the methodology to the world's 66 currently defined Large Marine Ecosystems. The method relies on a large number of spatial and temporal databases, including FishBase, SeaLifeBase, as well as several other databases developed notably as part of the Sea Around Us project. The models are formulated using the freely available Ecopath with Ecosim (EwE) modeling approach and software. We tune the models by fitting to available time series data, but recognize that the models represent only a first-generation of database-driven ecosystem models. We use the models to obtain a first estimate of fish biomass in the world's LMEs. The biggest hurdles at present to further model development and validation are insufficient time series trend information, and data on spatial fishing effort.     

Efficient and sustainable environmental management as a means of addressing current pollution issues

Environmental Science and Pollution Research -     

Assessing the alteration of physicochemical characteristics in composted organic waste in a prototype decentralized composting facility

Environmental Science and Pollution Research - This article presents the pilot experience of an integrated biowaste management system developed in Tinos island, Greece, which promoted source...     

Removal of pathogens from greywater using green roofs combined with chlorination

Environmental Science and Pollution Research - Greywater is an important alternative water resource which could be treated and reused in buildings, reducing the freshwater demand in drought...     

Systematic characterization and chemical treatment of olive oil mill wastewater

Classic and centrifugal olive oil mill wastewater volumes of 1.18 and 1.68m³/Mg olives and corresponding polluting loads of 37 and 53 Kg BOD₅ and 82 and 121 Kg COD/Mg olives were established in a systematic study of 15 mills. Lime treatment at an optimum pH level near 11 requiring a dose less than 10g/l effected COD removals from 15 to 22% for classic and from 33 to 46% for centrifugal mill waste. The volume of resulting sludge was large and could not be adequately handled by sedimentation; the sludge had good dewatering characteristics and was amenable to simple straining. Excess lime treatment using up to 50 g/l lime offered little additional benefit.