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Abstract This work introduces an assessment of the projected climatic changes in wind characteristics in Greece through the WRF model 5 × 5 km2, forced by the EC-EARTH Global Climate Model (GCM). Firstly, the model is validated against historic observations at 10 m, before being applied to the Representative Concentration Pathways (RCPs) 4.5 and 8.5 that represent an average expected future and a worst-case scenario. Projected changes in the mean annual wind speed at 100 m, between the historic (1980–2004) and future (2020–2044) scenarios are found to vary locally between −5% and +20%, whereas for the Wind Energy Density (WED) this variation lies between −15% and +60%. Overall, robust and significant increases regarding the mean wind speeds were found mainly over the north and central-western Aegean region, the Island of Crete, as well over Greek mainland and the Ionian Sea. Both scenarios predicted higher statistically significant increases in the Weibull shape parameter values (of about 0.2) in the north–central Aegean, while the summer seasonal analysis, yielded significant decreases over the western Ionian Sea and south and south-western parts of Crete, which might be indicative of more gusty events. Finally, extreme wind speeds analysis indicated increases, which might affect wind turbines structural integrity.

Abstract This work introduces an assessment of the projected climatic changes in wind characteristics in Greece through the WRF model 5 × 5 km2, forced by the EC-EARTH Global Climate Model (GCM). Firstly, the model is validated against historic observations at 10 m, before being applied to the Representative Concentration Pathways (RCPs) 4.5 and 8.5 that represent an average expected future and a worst-case scenario. Projected changes in the mean annual wind speed at 100 m, between the historic (1980–2004) and future (2020–2044) scenarios are found to vary locally between −5% and +20%, whereas for the Wind Energy Density (WED) this variation lies between −15% and +60%. Overall, robust and significant increases regarding the mean wind speeds were found mainly over the north and central-western Aegean region, the Island of Crete, as well over Greek mainland and the Ionian Sea. Both scenarios predicted higher statistically significant increases in the Weibull shape parameter values (of about 0.2) in the north–central Aegean, while the summer seasonal analysis, yielded significant decreases over the western Ionian Sea and south and south-western parts of Crete, which might be indicative of more gusty events. Finally, extreme wind speeds analysis indicated increases, which might affect wind turbines structural integrity.

Time series has been a popular tool for the analysis and forecasting of a large number of data. Very often, the applied approaches forecasts had limited success and the main reason was the lack of statistically significant historical information. We focus our attention on three common series, which are formed from the averaging of data collected over a shorter time interval. These include weekly and biweekly foreign exchange rates, mean hourly wind speed and electric load data. The proposed scheme, which takes advantage of the dominant characteristics of the shorter interval data, produced superior forecasts to those based on conventional approaches based only on historical observations of the target data. In the first two series, the proposed approach generated forecasts that significantly lower to those of the trivial random walk, a benchmark in series dominated by short-term correlation. On the load series, this approach made possible that a simple auto-regressive model returned lower forecasting error compared to a neural network that included special indicators to account for the periodic nature of the data.

Time series has been a popular tool for the analysis and forecasting of a large number of data. Very often, the applied approaches forecasts had limited success and the main reason was the lack of statistically significant historical information. We focus our attention on three common series, which are formed from the averaging of data collected over a shorter time interval. These include weekly and biweekly foreign exchange rates, mean hourly wind speed and electric load data. The proposed scheme, which takes advantage of the dominant characteristics of the shorter interval data, produced superior forecasts to those based on conventional approaches based only on historical observations of the target data. In the first two series, the proposed approach generated forecasts that significantly lower to those of the trivial random walk, a benchmark in series dominated by short-term correlation. On the load series, this approach made possible that a simple auto-regressive model returned lower forecasting error compared to a neural network that included special indicators to account for the periodic nature of the data.

The impacts of climate change are anticipated to become stronger in the future, leading to higher costs and more severe accidents in the oil industry’s facilities and surrounding communities. Motivated by this, the main objective of this paper is to develop, for the oil industry, a risk assessment methodology that considers future climate projections. In the context of an action research effort, carried out in a refinery in Greece, we adapted the organization’s extant risk management approach based on the Risk Assessment Matrix (RAM) and suggested a risk quantification process that incorporates future climate projections. The Climate Risk Assessment Matrix (CRAM) was developed to be used to assess the exposure of the facility’s assets, including human resources, to future climate risks. To evaluate CRAM, a comparison with RAM for the specific organization for the period 1980–2004 was made. Next, the application of CRAM for the period 2025–2049 indicated that, even though the resilience of the operations of the company to extreme conditions seems adequate at present, increased attention should be paid in the future to the resilience of refinery processes, the cooling system, and human resources. Beyond the specific case, the paper provides lessons for similar organizations and infrastructures located elsewhere.

The impacts of climate change are anticipated to become stronger in the future, leading to higher costs and more severe accidents in the oil industry’s facilities and surrounding communities. Motivated by this, the main objective of this paper is to develop, for the oil industry, a risk assessment methodology that considers future climate projections. In the context of an action research effort, carried out in a refinery in Greece, we adapted the organization’s extant risk management approach based on the Risk Assessment Matrix (RAM) and suggested a risk quantification process that incorporates future climate projections. The Climate Risk Assessment Matrix (CRAM) was developed to be used to assess the exposure of the facility’s assets, including human resources, to future climate risks. To evaluate CRAM, a comparison with RAM for the specific organization for the period 1980–2004 was made. Next, the application of CRAM for the period 2025–2049 indicated that, even though the resilience of the operations of the company to extreme conditions seems adequate at present, increased attention should be paid in the future to the resilience of refinery processes, the cooling system, and human resources. Beyond the specific case, the paper provides lessons for similar organizations and infrastructures located elsewhere.

Abstract Under its Kyoto and EU obligations, Greece has committed to a greenhouse gas (GHG) emissions increase of at most 25% compared to 1990 levels, to be achieved during the period 2008–2012. Although this restriction was initially regarded as being realistic, information derived from GHG emissions inventories shows that an increase of approximately 28% has already taken place between 1990 and 2005, highlighting the need for immediate action. This paper explores the reallocation of production in Greece, on a sector-by-sector basis, in order to meet overall demand constraints and GHG emissions targets. We pose a constrained optimization problem, taking into account the Greek environmental input–output matrix for 2005, the amount of utilized energy and pollution reduction options. We examine two scenarios, limiting fluctuations in sectoral production to at most 10% and 15%, respectively, compared to baseline (2005) values. Our results indicate that (i) GHG emissions can be reduced significantly with relatively limited effects on GVP growth rates, and that (ii) greater cutbacks in GHG emissions can be achieved as more flexible production scenarios are allowed.

Abstract Under its Kyoto and EU obligations, Greece has committed to a greenhouse gas (GHG) emissions increase of at most 25% compared to 1990 levels, to be achieved during the period 2008–2012. Although this restriction was initially regarded as being realistic, information derived from GHG emissions inventories shows that an increase of approximately 28% has already taken place between 1990 and 2005, highlighting the need for immediate action. This paper explores the reallocation of production in Greece, on a sector-by-sector basis, in order to meet overall demand constraints and GHG emissions targets. We pose a constrained optimization problem, taking into account the Greek environmental input–output matrix for 2005, the amount of utilized energy and pollution reduction options. We examine two scenarios, limiting fluctuations in sectoral production to at most 10% and 15%, respectively, compared to baseline (2005) values. Our results indicate that (i) GHG emissions can be reduced significantly with relatively limited effects on GVP growth rates, and that (ii) greater cutbacks in GHG emissions can be achieved as more flexible production scenarios are allowed.

This work presents the methodological approach followed for the study of the interaction of natural stone monuments with the local microclimate (exposure to RH, temperature alterations, wind, marine aerosol). This was implemented with the documentation of the associated weathering phenomena and the study of historic climate data of the area. The paper is focused on the main weathering mechanisms of the marly limestone at the Hellenistic theater of Zea in Piraeus, Greece. Based on the weathering phenomena identified, the development of the appropriate mitigation strategy was based on the physical, chemical and mechanical characterization of the natural stones, along with the evaluation of different conservation treatments, considering the characteristics of the coastal environment. Considering the mineralogy of marly limestones, silane-based materials were selected for providing both consolidation and water repellency effects. The evaluation of the conservation treatments was based on the modification of microstructural and water-related properties of natural stone samples, along with their consequent effect on their durability against accelerated aging tests. The results indicated that the design of migration actions proved to be multivariable parameter, depending on the intrinsic stone properties, the environmental parameters and the conservation efficacy of the treatments.