Kostas D. Karatzas

Feasibility of energy saving renovation measures in urban buildings: The impact of energy prices and the acceptable pay back time criterion

Abstract The energy renovation of existing buildings is an important tool for the reduction of energy consumption in the building sector, the improvement of prevailing indoor thermal comfort conditions and also for the improvement of environmental conditions in urban areas. At the same time, it is a technical, economic and social problem, due to the way in which many cities have been built and the restrictions imposed by economic constrains that tantalise most countries in South-Eastern Europe, and also Greece. It applies particularly in Northern Greece, with its cold and prolonged heating season, where a series of studies was carried out since 1994 to approach the problem and develop viable proposals. Public and mixed-use buildings form a significant part of the building stock and are therefore a primary candidate for energy saving measures, especially as they also play the role of a ‘pilot-demonstrator’ for the private owned buildings. However, due to the low energy prices that prevailed over the last 10 years, and as energy saving measurements are capital intensive investments, little was done in that direction. The recent sharp increase in oil prices proved that this was a short-sighted policy. In the following paper are presented the results of a study that aimed to determine the potential of energy saving renovation measures, in a representative sample of buildings under realistic conditions, to evaluate the feasibility of these measures, and also the way in which this feasibility is being analysed, under the rapidly changing economic conditions.

Intercomparison of air quality data using principal component analysis, and forecasting of PM10 and PM2.5 concentrations using artificial neural networks, in Thessaloniki and Helsinki

In this paper we propose a methodology consisting of specific computational intelligence methods, i.e. principal component analysis and artificial neural networks, in order to inter-compare air quality and meteorological data, and to forecast the concentration levels for environmental parameters of interest (air pollutants). We demonstrate these methods to data monitored in the urban areas of Thessaloniki and Helsinki in Greece and Finland, respectively. For this purpose, we applied the principal component analysis method in order to inter-compare the patterns of air pollution in the two selected cities. Then, we proceeded with the development of air quality forecasting models for both studied areas. On this basis, we formulated and employed a novel hybrid scheme in the selection process of input variables for the forecasting models, involving a combination of linear regression and artificial neural networks (multi-layer perceptron) models. The latter ones were used for the forecasting of the daily mean concentrations of PM₁₀ and PM₂.₅ for the next day. Results demonstrated an index of agreement between measured and modelled daily averaged PM₁₀ concentrations, between 0.80 and 0.85, while the kappa index for the forecasting of the daily averaged PM₁₀ concentrations reached 60% for both cities. Compared with previous corresponding studies, these statistical parameters indicate an improved performance of air quality parameters forecasting. It was also found that the performance of the models for the forecasting of the daily mean concentrations of PM₁₀ was not substantially different for both cities, despite the major differences of the two urban environments under consideration.

Air pollution modelling with the aid of computational intelligence methods in Thessaloniki, Greece

Abstract Air pollution modelling is necessary for simulating the atmospheric environment system in terms of pollutants and meteorological conditions, taking into account the nonlinearities of the underlying phenomena. In the current paper, Artificial Neural Networks are used for modelling ozone, and for simulating its behaviour in relation to other atmospheric parameters of interest, for the city of Thessaloniki, Greece. This behaviour is also investigated with the aid of Principal Component Analysis (PCA). Results suggest the operational capabilities of such models, and the research potential in the application of computational intelligence methods for the environmental sector.

Assessing the impact of the new Athens airport to urban air quality with contemporary air pollution models

The new airport of Athens will be constructed in the Spata area to the east of the Athens basin. In an attempt to study how the airport operation influences air quality in Athens, the wind flow and pollutant transport in the Athens basin and the Spata area are studied by applying a set of contemporary models, all constituents of the EUMAC Zooming Model (EZM): (1) the nonhydrostatic prognostic mesoscale model MEMO for simulating air flow and the dispersion of inert pollutants, and (2) two photochemical dispersion models, the three-dimensional model MARS and the three-layer model MUSE for describing the dispersion of reactive pollutants. Simulations were performed for meteorological conditions favouring the occurrence of air pollution episodes. Emphasis is put on the influence of the airport emissions on air quality assuming that the airport is operating either at its old location (Hellenikon) or at Spata. Comparison of simulation results for one selected scenario achieved with all three models reveals similar diurnal variations of nitrogen oxides in the Athens basin and the Spata area. The model results show that under conditions favoring air mass penetration from Athens to the Spata area the resulting pollutant transport causes an increase in air pollution levels without, however, leading to the exceedance of air quality standards. In the opposite case, the pollutant transport cannot have a noticeable adverse influence on the Athens air quality because of both the relatively high urban air pollution levels and the fact that the penetration depth is small.

Monitoring, Modelling and Forecasting of the Pollen Season

The section about monitoring covers the development of phenological networks, remote sensing of the season cycle of the vegetation, the emergence of the science of aerobiology and, more specifically, aeropalynology, pollen sampling instruments, pollen counting techniques, applications of aeropalynology in agriculture and the European Pollen Information System. Three data sources are directly related with aeropalynology: phenological observations, pollen counts and remote sensing of the vegetation activity. The main future challenge is the assimilation of these data streams into numerical pollen forecast systems. Over the last decades consistent monitoring efforts of various national networks have created a wealth of pollen concentration time series. These constitute a nearly untouched treasure, which is still to be exploited to investigate questions concerning pollen emission, transport and deposition. New monitoring methods allow measuring the allergen content in pollen. Results from research on the allergen content in pollen are expected to increase the quality of the operational pollen forecasts.

Air Quality Modeling

Air pollution modeling (APM) is being developed and used in order to better understand, investigate, assess, and regulate the quality of the atmospheric environment and the distribution of toxic pollutants which are often used in ecotoxicology. Atmospheric models are also used to assess the impact of air pollutants on human health. In this respect, APM covers a very complex and interdisciplinary scientific area, where aspects of environmental policy and decision making mix together with aspects like remote sensing, land-use impact, initial and boundary conditions, data assimilation techniques, chemical schemes, comparison methods between data measured and data modeled, computational efficiency and performance, coupling with the meteorology, long-range transport impact on local air pollution, new satellite data assimilation techniques, real-time and forecasting air quality modeling and sensitivity analysis, and many others. APM has progressed significantly during the last two decades, attracting the interest of various research groups and initiatives worldwide. It covers all aspects related to the life cycle of pollutants, starting from their emission or ‘production’ within the atmosphere, and ending with their impacts on man and the ecosystem. This field of science is interested to describe the generation, transportation, dispersion, physical and chemical transformation, and the impact of various categories of substances that are identified and classified as air pollutants via the environmental legal framework and the scientific community. It should be noted that air pollution is very much related to meteorological fields, since the atmosphere is governed by the general fluid mechanics laws described by the Navier–Stokes equation system, while progress in computer performance during the last decades has substantially impelled the research on air quality modeling in a parallel way. This contribution focuses on providing a general overview of the state of the art on air quality modeling, from the point of view of the ‘user community’, that is, policy makers, urban planners, environmental managers, etc. It also tries to bring to the discussion key questions concerning the air quality modeling success in usage, such as: identification of uncertainties in emission inventories and meteorological fields, capability of simulating pollutants like urban aerosols, the next-generation developments in models to answer new scientific questions, etc.

A modelling study of an extraordinary night time ozone episode over Madrid domain

AbstractDuring the early morning hours on April 29, 2000, a time series of ozone observations from several stations showed that a uniqueand exceptional ozone episode occurred in Madrid city and surrounding areas, whereby monitoring stations reported ozoneconcentrations up to 1190 mg/m 3 . In order to investigate this phenomenon, two different air quality modeling approaches are usedhere:U The FLEXTRA trajectory model was initially used, suggesting that an intrusion of stratospheric air occurred over the Madridarea and brought stratospheric air down to 1000e2000 m AGL. The local circulation system, not resolved by the FLEXTRAtrajectories, subsequently brought some of this stratospheric air to the surface. However, the maximum ozone concentrationthat could be explained by this process is much less than the observed one.U The OPANA Air Quality Modeling System was also employed to study air quality over the Madrid community and citydomains. Results suggested that the main wind direction returned to Madrid after 180( wind change direction 1 to 2 h beforethe ‘‘episode’’, bringing back ozone generated the day before (typical weekend day with high traffic density). On the other hand,convergence of winds along the South-West North-East axis over the Madrid community showed an important correspondencewith the sequence of observations.Preliminary conclusions show that the exceptional meteorological conditions on such a night could be reason for the occurrenceof high values. Additional technical circumstances (such as technical incidences in some monitoring stations) also suggest that someinstruments did not work properly under these high concentrations and, thus, real ozone concentrations may have been lower thanthose measured. 2004 Elsevier Ltd. All rights reserved.

Providing multi-modal access to environmental data—customizable information services for disseminating urban air quality information in APNEE

Abstract APNEE (Air Pollution Network for Early warning and online information Exchange in Europe) is establishing a uniform information portal on air quality in different European regions. Rather than elaborating sophisticated air quality management and forecasting approaches, APNEE is striving to develop a technical umbrella for the distribution and customization of existing air quality management systems. It employs several communication channels—including short message services, mobile communication protocols, and street panels—to transmit information on air quality to selected citizens in urban regions in a customized fashion, tailoring the information content (i.e. the kind of warnings or recommendations for further actions) to the user group registered, to the technical capabilities of the end-user devices targeted, and of course to the geographic location. APNEE will study the feasibility of different broadcasting methods and evaluate them with regard to acceptability, potential impact on citizen behaviour, future markets for online environmental information services for city authorities, telecommunication service providers and other entrepreneurs in the information society. Overall, APNEE will provide an enabling technology to implement European directives and national legislation for online dissemination of air quality information.

Personalized pollen-related symptom-forecast information services for allergic rhinitis patients in Europe.

We report on the development of personalized pollen‐related information services that include sensitivity categorization, threshold identification, and symptom forecasting, addressing patients with allergic rhinitis in Europe.

Identification of major components for integrated urban air quality management and information systems via user requirements prioritisation

Abstract Integrated environmental management and information systems are software applications with various components. In the current paper the identification of the major components of such systems is being performed with the aid of the prioritisation of user requirements. For this reason, the analytical hierarchy process is applied for an integrated urban air quality management and information system, which is developed as a portal for environmental information. Useful results are drawn regarding the relevant importance of the components of such systems and the sensitivity of the prioritisation during their selection as a function of their relevant cost and value.