Environmental data analysis and modelling

Climate change and atmospheric nitrogen deposition can impact the integrity of ecosystems. Therefore, the EU Biodiversity Strategy foresees that Member States map and assess the state of ecosystems and their services in their national territory. By example of Germany, this article presents a quantitative, spatially explicit as well as nationally, regionally and site-specifically applicable methodology for classifying and mapping forest ecosystems and identifying changes of their integrity comparing their reference states (1961-1990) with measured (1991-2010) und potential future conditions (2011-2017). To this end, measured environmental data were complemented by dynamic modelling of future climate and soil conditions. A fuzzy rule-based model for estimating spatial patterns and temporal trends of soil moisture was developed and tested at the federal and regional level. Forest ecosystem conditions were evaluated and ordinated at three levels (indicators, functions and ecosystem type) with regard to functionality, chemical and biological characteristics, stress tolerance against climate change and nitrogen deposition scenarios for the years 1961-1990, 1991-2011 and 2011-2070.

Session: 36, Room: F, at Fri, 09/06/2019 - 15:45 to 16:00
Oral presentation in Environmental data analysis and modelling

Nestos Delta (north Greece) is a complex ecosystem of high ecological importance, protected by the European Union as a Natura 2000 site. The presence of the habitats 3170* and 91E0*, which are highly connected with water resources availability, impose the continuous monitoring of precipitation in the area, since even minor changes of the precipitation regime could have a significant effect on the habitats’ viability. Aim of this work is to detect significant precipitation changes by analyzing datasets from 5 nearby station for a time period of about 50 years. The results indicate statistically significant decreasing changes mainly at lower altitudes, and increasing at higher.

Session: 36, Room: F, at Fri, 09/06/2019 - 16:09 to 16:12
Flash presentation in Environmental data analysis and modelling

Climate change and its impact on everyday life still remains one of the greatest challenge of our era. The complex nature of climate data addresses the use of data science techniques to provide predictive analytics to the task at hand. While most existing approaches exploit correlation between observations and features to improve forecasting, the present work deals with causality, a principle that enhances robustness and provides better insight to domain experts. More specifically, a novel framework for causality discovery is proposed, based on statistical (i.e. Granger causality tests) as well as on non-linear state space reconstruction algorithms (i.e. Convergent Cross Mapping, a very effective algorithm in dynamic systems, such as the task at hand) in order to find the causal relations between meteorological time series. Furthermore, the framework also supports methods for graph analysis, thus providing informative visualizations on the influential levels of causality. Experiment results on a dataset of real observations from different cities of Greece, obtained through crawling of Internet sites of Davis weather stations demonstrate the ability to model and visualize the relations of the meteorological parameters amongst the cities. Moreover, by utilizing such causal inference knowledge, the forecasting performance for each city is significantly improved, since only relevant and informative features were taken into consideration.

Session: 36, Room: F, at Fri, 09/06/2019 - 15:00 to 15:15
Oral presentation in Environmental data analysis and modelling

The standard method for the estimation of reference evapotranspiration (ETo) is FAO-Penman-Monteith (FAO56-PM). However, it requires various climatic parameters which are often hard to achieve due to various reason. In order to bridge this gap an alternative equation has to be find out. The main aim of this research work was to assess the performance of the various mass transfer-based method with respect to standard FAO56-PM. Daily meteorological data from 1980 to 2018 has been used to compute reference evapotranspiration. Daily ETo values were computed. Among the computed values 70% of them were used to calibrate the mass transfer equations under study and remaining 30 % data were used to validate the calibrated equation against the standard method. The calibrated models were analysed and compared using statistical tools and ranked using Global Performance Indicator where a higher value represented a model’s better performance. The models were then arranged using GPI and it was found that Albrecht model resulted in best estimation capability. The results of this study could be used by the water management system, crop cultivators, crop advisors, researchers and students from universities and research centres. Moreover, it is beneficial for the decision maker in the vast field of agriculture, hydrology and environment.

Session: 36, Room: F, at Fri, 09/06/2019 - 15:30 to 15:45
Oral presentation in Environmental data analysis and modelling

In recent years a major scientific effort has been focused on the protection of marine mammals. Gulf of Corinth is part of the Natura 2000 network (GR2530007) since 2016, with Special Areas of Conservation and constitutes an important habitat for striped dolphin (Stenella coeruleoalba), bottlenose dolphin (Tursiops truncatus) and short-beaked common dolphin (Delphinus delphis).

This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Program «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Biomonitoring of marine mammals in Eastern Mediterranean” (MIS 5005612).

Session: 30, Room: F, at Fri, 09/06/2019 - 12:45 to 13:00
Oral presentation in Environmental data analysis and modelling

The presented study considers the numerical modelling of a thermal bridge distribution, based on conjugated heat transfer and Computational Fluid Dynamics (CFD) model of approximated external concrete wall. The thermal bridge distribution is cross-analyzed relative to the indoor and outdoor air parameters, under the corresponding structure’s thermal properties. The main analyzed parameters in the study are the surface temperature on the exterior wall, outdoor air temperature and wall thermal conductivity. The integrated modeling results show the complex environmental impact over the generic conditions for the thermal bridge existence. The further analyses will include the relative humidity and dew point temperature impact over the thermal bridge distribution. These additional parameters may be used for moisture accumulation indicator, in the developed numerical model.

Session: 30, Room: F, at Fri, 09/06/2019 - 12:30 to 12:45
Oral presentation in Environmental data analysis and modelling

In the building structure, the “thermal bridge” is defined as an isolated zone, where construction elements have higher thermal conductivity, compared with the rest of the building envelope. Thus, a significant temperature difference may exist between adjacent solid and air volumes within the developments, especially in winter conditions. The existence of thermal bridge mostly affects the energy performance of buildings, due to the increased heat losses from the occupied spaces. But also, the decreased surface temperature in these zones, could lead to moisture accumulation and substantial humidity related problems in the indoor environment.
Considering these important effects, the presented study describes the development of numerical model of a thermal bridge distribution, based on conjugated heat transfer in concrete external wall section. The thermal bridge distribution is analyzed relative to the indoor and outdoor air parameters, and the envelope thermal properties. The achieved surface temperature sensitivity results may be used for further moisture accumulation model development or enhancements.

Session: 36, Room: F, at Fri, 09/06/2019 - 16:06 to 16:09
Flash presentation in Environmental data analysis and modelling

Eight nuclear abnormalities of geno-cytotoxicity were studied in peripheral blood erythrocytes of herring (Clupea harengus membras), flounder (Platichthys flesus) and Atlantic cod (Gadus morhua) sampled (2010–2017) from the Polish and the Lithuanian Exclusive Economic Zones (EEZs) in the Baltic Sea. At all study stations, total genotoxicity (∑Gentox) were found to be higher than total cytotoxicity (∑Cytox). A significant time-related decrease in genotoxicity was detected in the Lithuanian EEZ (2015–2017), while in the Polish EEZ (2014–2016), the opposite tendency was revealed. The highest ∑Gentox and ∑Cytox values recorded in the fish sampled at the study stations located relatively close to each other clearly indicate an increased environmental geno-cytotoxicity pressure for fish in these areas. Exceptionally high and high level genotoxicity risks to herring followed by those to flounder and cod were determined at a higher percentage of the stations studied.

Session: 36, Room: F, at Fri, 09/06/2019 - 15:15 to 15:30
Oral presentation in Environmental data analysis and modelling

Through this research, we aim to develop a methodology for estimating the contribution of the natural and anthropic factors to the spatial variation of Total Dissolved Solids (TDS). The study area is Jiu River Basin, a Danube tributary from SW Romania.
TDS content was measured on Jiu River and its main tributaries, in periods of low waters in the summer of 2017 and 2018. For the area upstream each point, the following factors considered as primarily responsible for the TDS concentration were mapped and integrated in GIS and statistical analysis: geology, vegetation, soil textures, relevant human activities (coal-mining industry and agriculture in the valleys and in the catchments upstream the measuring points).
Using the principal component analysis (PCA) and regression models, scores were assigned to quantify the contributions to the spatial variation of TDS in the rivers. The results showed that coal mining and lithology (marls’ dominance) play the main role in explaining the TDS variation.
The development of such an integrated methodology improved the understanding of the relationship between the rivers’ TDS and the environmental drivers.

Session: 36, Room: F, at Fri, 09/06/2019 - 16:03 to 16:06
Flash presentation in Environmental data analysis and modelling

Computational budget is a severe limitation on the automatic calibration of expensive hydrodynamic and water quality models. To tackle this limitation, the present work formulated a metamodeling-based approach for parameter estimation of such models and assessed the computational gains of this approach compared to a benchmark alternative (a derivative-free optimization method). A response surface proxy of the original model was designed to emulate the behavior of the underlying system, employing Latin hypercube sampling as a strategy for the design of computer experiments and kriging as the technique for the analysis of computer experiments. The response surface proxy of the original model was employed in the automatic fine-tuning of model parameters and, finally, the computational gain over the benchmark alternative was estimated. The metamodeling-based approach was tested in the calibration of the hydrodynamic and water quality models of two water reservoirs. The benchmark alternative analysis indicated that the metamodeling-based approach required 20% to 38% less function evaluations to reach a solution with the same quality compared to the benchmark alternative.

Session: 30, Room: F, at Fri, 09/06/2019 - 12:15 to 12:30
Oral presentation in Environmental data analysis and modelling

Seasonally dry tropical forest (SDTF) at the Colombian inter-Andean valley of Cauca River (IVCR) has been under constant transformation. Following the current SDTF’s global distribution, it has remained as small and sparse fragments embedded in an anthropogenic landscape. Information regarding the known species composition is a basic input in any modelling scheme. Environmental data is also needed to understand its influence as an explanatory variable for the species occurrences. Knowledge about the biomes and ecoregions where they have been registered may help to understand the way in which the multiple species have been distributed through environmental gradients. In such a way we could recognize the relevance that IVCR plays for the conservation of SDTF plant species in the long term. From multiple datasets, a database with 1725 plant species was built. After applying different criteria set (endangered, endemic, conservation status, at national and regional level), different species subsets were obtained. For a first subset with the species prioritized, Maxent Algorithm on R Studio has been applied to produce predictive habitat suitability models to support the detection of potential areas for restoration. Restoration scenarios will be built for each subset of prioritized species which can be used for landscape planning purposes.

Session: 36, Room: F, at Fri, 09/06/2019 - 16:00 to 16:03
Flash presentation in Environmental data analysis and modelling

One of the most challenging tasks in potable water production is the cost-efficient and consistent operation of water treatment plants (WTPs) that treat raw water of variable quality and quantity. To increase process stability and optimize the usage of resources, two data-driven models simulated coagulation in two WTPs. The data-driven models were successfully trained on monitoring data collected from the two WTPs (mean errors of effluent turbidity were below 0.5 NTU in both case studies) and were subsequently employed in the optimization of two historical periods of the WTPs. During this model-based backtesting of the WTPs, multiple operating scenarios were investigated on a daily time step in search of chemical doses that deliver a quality threshold for treated water at the minimum usage of chemicals. Results from the application of this model-based approach for WTP optimization indicated that a reduction of chemical costs equal to 6 % and 8 % would be probable for the two case studies respectively, without hampering the efficiency of raw water treatment. This work underscores that the large quantity of passive data that are amassed daily during the operation of WTPs can be turned into actionable intelligence that supports decision-making and enhances adaptive planning for water utility operators.

Session: 30, Room: F, at Fri, 09/06/2019 - 12:00 to 12:15
Oral presentation in Environmental data analysis and modelling

The present paper focuses on the development of a methodology that simulates micrometeorological thermal conditions in an urban context based on weather station data. The micrometeorological conditions at Syntagma square, the central square of Athens, Greece were simulated by ENVI-met software in order to evaluate the thermal conditions experienced by its users. Located in the heart of city’s commercial activity, the square attracts many visitors, especially during summer months, when extreme thermal conditions could be encountered. ENVI-met can simulate the necessary factors for the estimation of thermal sensation through thermal indices, i.e. air temperature, mean radiant temperature, relative humidity, and wind speed. The meteorological data needed as input were obtained from the nearest weather station. In-situ micrometeorological measurements recorded at the height of 1.1m, were used to validate the simulated results. ENVI-met simulations were performed at a high spatial and temporal resolution. The appropriate adjustments were made to the modeling procedure to achieve a successful and resource-effective simulation.

Session: 30, Room: F, at Fri, 09/06/2019 - 13:06 to 13:09
Flash presentation in Environmental data analysis and modelling

Environmental innovation is considered one of the key drivers of sustainable development and economic growth. However, we still know very little about the organizational factors underling the development of this category of innovations and their relative competitive effect. In this paper, we focus on regions and we look at the specific effect of environment-related technologies and collaborative environmental inventions on the competitiveness of European regions. In fact, the complex and multidisciplinary nature of environmental innovation is expected to further strengthen the competitive advantage of regions and the strategic significance of geographical proximity. A longitudinal study of 232 European regions over the period 2000-2013 was organized using data from the RegPat, Cambridge Econometrics and Eurostat databases. Our main results confirm the positive effect of environment-related technologies and local collaborative networks on regional competitiveness with significant implications in terms of policy making.

Session: 30, Room: F, at Fri, 09/06/2019 - 13:09 to 13:12
Flash presentation in Environmental data analysis and modelling

In the last years, exploitation of the wind power has been constantly increasing together with the size of the turbines. Furthermore, by 2030 wind energy is expected to supply around 30% of EU’s power demand. Offshore wind represents a significant future opportunity, since resources are abundant and more stable. In the North and Baltic seas more experience is gained on bottom fixed turbines, but also many initiatives emerge to accelerate the development of floating devices, such as the projects in the Mediterranean and Atlantic. From this perspective, the objective of this work is to analyze the expected dynamics of the of the wind conditions in the European coastal environment of the Mediterranean Sea. The study is focused on estimating the average and extreme wind speeds for the 30-year time interval 2021-2050. In parallel, an analysis of the historical wind data for the 30-year period 1976-2005 is also performed. The climatic wind fields provided by the Global Change Assessment Model are considered in the analysis under the Representative Concentration Pathway scenario 4.5. This is the most probable scenario and assumes that the CO2 emissions will increase until 2040 and then decline.

Session: 30, Room: F, at Fri, 09/06/2019 - 13:00 to 13:03
Flash presentation in Environmental data analysis and modelling

Currently, the priority in the EU countries is the subject of unemployment, due to the economic and social situation in many countries and young people unemployment. Although unemployment in some other counties has dropped, it is still quite high. The new economic models based on heterodox economics point to some new and innovative solutions in this area, among others - creating new green jobs. Green employment is the beginning of new solutions that accept the principles of sustainable development, and the green economy, which creates new companies. New professions, as well as new jobs, are created by green organizations which, after brown organizations, are the next stage in the development of human consciousness in the context of sustainable development. The article presents the idea of green jobs as solution of unemployment problem and development of an economic sector that is vital for Europe's transition towards a circular and efficient low-carbon economy.

Session: 30, Room: F, at Fri, 09/06/2019 - 13:03 to 13:06
Flash presentation in Environmental data analysis and modelling