Linking Hydrogeological and Ecological Tools for an Integrated River Catchment Assessment

Ecological (biological and hydrochemical assessment) and hydrogeological (vulnerability and pollution risk mapping) tools have been combined to assess the ecological quality and hydrogeological vulnerability of an agricultural river basin. In addition, the applicability of the recently developed vulnerability assessment approach (COP method) in the particular environmental conditions was tested by comparing its results with hydroecological assessment tools (i.e., pollution metrics). Five sampling sites were selected and sampled for benthic macroinvertebrates and physicochemical variables during summer and spring. Overall, sites ranged from moderate to poor ecological quality. The results illustrated that 26% of the study area was of moderate pollution risk, while 65% was classified as of low and very low risk zones. However, the higher elevation zones where calcareous rock formations are encountered presented moderate to high pollution risk that was accredited by the ecological quality assessment. Pollution metrics facilitated from hydrochemical analysis indicated a significant association with groundwater vulnerability, thus validating vulnerability and risk estimations. This study indicated that the particular groundwater pollution risk mapping methodology and the water quality assessment indices can be well combined to provide an integrated evaluation tool at a catchment scale.     

A Combined MOIP–MCDA Approach to Building and Screening Atmospheric Pollution Control Strategies in Urban Regions

This article presents a methodological approach for the formulation of control strategies capable of reducing atmospheric pollution at the standards set by European legislation. The approach was implemented in the greater area of Thessaloniki and was part of a project aiming at the compliance with air quality standards in five major cities in Greece. The methodological approach comprises two stages: in the first stage, the availability of several measures contributing to a certain extent to reducing atmospheric pollution indicates a combinatorial problem and favors the use of Integer Programming. More specifically, Multiple Objective Integer Programming is used in order to generate alternative efficient combinations of the available policy measures on the basis of two conflicting objectives: public expenditure minimization and social acceptance maximization. In the second stage, these combinations of control measures (i.e., the control strategies) are then comparatively evaluated with respect to a wider set of criteria, using tools from Multiple Criteria Decision Analysis, namely, the well-known PROMETHEE method. The whole procedure is based on the active involvement of local and central authorities in order to incorporate their concerns and preferences, as well as to secure the adoption and implementation of the resulting solution.     

Chemical characterisation of particulate matter in urban transport modes

Traffic is a main source of air pollutants in urban areas and consequently daily peak exposures tend to occur during commuting. Personal exposure to particulate matter (PM) was monitored while cycling and travelling by bus, car and metro along an assigned route in Lisbon (Portugal), focusing on PM2.5 and PM10 (PM with aerodynamic diameter <2.5 and 10 µm, respectively) mass concentrations and their chemical composition. In vehicles, the indoor-outdoor interplay was also evaluated. The PM2.5 mean concentrations were 28?±?5, 31?±?9, 34?±?9 and 38?±?21?µg/m³ for bus, bicycle, car and metro modes, respectively. Black carbon concentrations when travelling by car were 1.4 to 2.0 times higher than in the other transport modes due to the closer proximity to exhaust emissions. There are marked differences in PM chemical composition depending on transport mode. In particular, Fe was the most abundant component of metro PM, derived from abrasion of rail-wheel-brake interfaces. Enhanced concentrations of Zn and Cu in cars and buses were related with brake and tyre wear particles, which can penetrate into the vehicles. In the motorised transport modes, Fe, Zn, Cu, Ni and K were correlated, evidencing their common traffic-related source. On average, the highest inhaled dose of PM2.5 was observed while cycling (55 µg), and the lowest in car travels (17 µg). Cyclists inhaled higher doses of PM2.5 due to both higher inhalation rates and longer journey times, with a clear enrichment in mineral elements. The presented results evidence the importance of considering the transport mode in exposure assessment studies.     

Groundwater risk assessment at a heavily industrialised catchment and the associated impacts on a peri-urban wetland

Industrial and agricultural activities often impose significant pressures to the groundwater quality and consequently degrade wetland ecosystems that depend mostly on subsurface water flow. Groundwater vulnerability and risk mapping is a widely used approach to assess the natural protection of aquifers and the associated pollution potential from human activities. In the particular study, the relatively new Pan-European methodology (COP method) has been applied in a highly industrialized peri-urban wetland catchment, located close to Athens city, to map the intrinsic vulnerability of the aquifer and evaluate the risk potential originating from local land uses. Groundwater analysis results for various parameters, including Phenols, PCBs and nutrients, have been used to validate the vulnerability and risk estimations while a biological assessment occurred to associate the mapping results with the wetland's ecological status. The results indicated that even though the natural protection of the aquifer is relatively high due to the dominant hydrogeologic and geomorphologic conditions, the groundwater pollution risk is considerable, mainly because of the existing hazardous land uses. The water quality of the groundwater accredited these findings and the ecological status of this peri-urban wetland also indicated significant impacts from industrial effluents.     

Chemical and ecotoxicological assessment of sludge-based biosolids used for corn field fertilization

Environmental Science and Pollution Research - Sludge-based biosolids can be used for crop fertilization and for soil enrichment with organic matter. The prerequisites for their application are...     

The future of transport-related emissions in dense urban areas: an analysis of various policy scenarios with MOLES

Environmental Economics and Policy Studies - Reducing air pollution is a major policy challenge, especially in densely populated urban areas where human exposure to emissions is considerable. This...     

A knowledge acquisition process to analyse operational problems in solid waste management facilities.

The available expertise on managing and operating solid waste management (SWM) facilities varies among countries and among types of facilities. Few experts are willing to record their experience, while few researchers systematically investigate the chains of events that could trigger operational failures in a facility; expertise acquisition and dissemination, in SWM, is neither popular nor easy, despite the great need for it. This paper presents a knowledge acquisition process aimed at capturing, codifying and expanding reliable expertise and propagating it to non-experts. The knowledge engineer (KE), the person performing the acquisition, must identify the events (or causes) that could trigger a failure, determine whether a specific event could trigger more than one failure, and establish how various events are related among themselves and how they are linked to specific operational problems. The proposed process, which utilizes logic diagrams (fault trees) widely used in system safety and reliability analyses, was used for the analysis of 24 common landfill operational problems. The acquired knowledge led to the development of a web-based expert system (Landfill Operation Management Advisor, http://loma.civil.duth.gr), which estimates the occurrence possibility of operational problems, provides advice and suggests solutions.     

Optimization of thermo-chemical hydrolysis of kitchen wastes

Municipal Solid Wastes (MSWs) in Greece consist mainly of fermentable organic material such as food scraps (～50%) and paper residuals (～20%). The aim of this work was to study the thermo-chemical pretreatment of the kitchen waste (KW) fraction of MSW focusing on biotechnological exploitation of pretreated wastes for biofuel production. A representative sample of municipal food residues was derived by combining weighted amounts of each individual type of residue recognized in daily samples obtained from the University of Patras’ students restaurant located at the Students Residence Hall (Greece). Chemical pretreatment experiments of the representative KW sample were performed using several types of chemical solutions (i.e. H₂SO₄, HCl, NaOH, H₂SO₃) of different solute concentration (0.7%, 1.5%, 3%) at three temperatures (50, 75, 120 °C) and a range of residence times (30–120 min). Optimized results proved that chemical pretreatment of KW, using either 1.12% HCl for 94 min or 1.17% HCl for 86 min (at 100 °C), increased soluble sugars concentration by 120% compared to untreated KW. The increase of soluble sugars was mainly attributed to the mono-sugars glucose and fructose.     

Neural Network Model for Predicting Peak Photochemical Pollutant Levels

ABSTRACT

In this paper, an attempt is made for the 24-hr prediction of photochemical pollutant levels using a neural network model. For this purpose, a model is developed that relates peak pollutant concentrations to meteorological and emission variables and indexes. The analysis is based on measurements of O₃ and NO₂ from the city of Athens. The meteorological variables are selected to cover atmospheric processes that determine the fate of the airborne pollutants while special care is taken to ensure the availability of the required input data from routine observations or forecasts. The comparison between model predictions and actual observations shows a good agreement. In addition, a series of sensitivity tests is performed in order to evaluate the sensitivity of the model to the uncertainty in meteorological variables. Model forecasts are generally rather insensitive to small perturbations in most of the input meteorological data, while they are relatively more sensitive in changes in wind speed and direction.