The objective of this study is to investigate the impact of the COVID-19 pandemic on the carbon footprint (CF) of two research projects. These projects were initiated prior to the onset of the pandemic and subsequently concluded afterward, serving as the Base Case (BC) for analysis. Furthermore, the study seeks to explore the potential applicability of measures implemented during the period of lockdown for future mitigation of CF. The applied methodology, which adheres to the guidelines provided by the GHG Protocol and the Department for Environment Food & Rural Affairs (DEFRA) emission factors, is utilized to examine the CF of the projects under two different scenarios. The first scenario assumes that the projects were implemented without the pandemic, while the second scenario considers that the projects were conducted entirely during the pandemic. Among the two projects under review, one emphasizes innovation and entails a collaboration between academia and business. This project is supported by a limited number of employees, exclusively from domestic partners. The other project is more oriented toward policy-making and involves a larger group of partners from Greece and Italy. Its main priority is dissemination. Carbon dioxide (CO₂) emissions associated with project activities mainly stem from electricity use, material consumption, project-hosted events, project participation in events, employees commuting, and equipment. Results show that in the first scenario, the projects exhibit a more than 40% increase in CO₂ emissions compared to the BC, while in the second scenario, the implementation of measures such as teleworking, virtual participation in events, and digitization of bureaucratic processes lead to a reduction in emissions by at least 20%. The study suggests that adopting such measures after the COVID-19 pandemic could significantly decrease greenhouse gas emissions.

The main objective of the present study is the development of an “on-line” heating emissions modeling system based on simulated meteorological data and its integration with air quality modeling systems in order to improve their accuracy. The WRF-CAMx air quality modeling system is applied over Greece for the cold period of 2015 (January–April, October–December) for two emissions scenarios: using the (a) “on-line” heating emissions based on WRF meteorology and (b) “static” heating emissions based on static temporal profiles. The monthly variation in total “on-line” heating emissions followed the temporal pattern of the air temperature over Greece, leading to the highest heating emissions in January and February, while higher differences in emissions between winter and spring/autumn months were identified in comparison with the static ones. The overall evaluation of the WRF-CAMx modeling system using the “on-line” heating emissions revealed satisfactory model performance for the mean daily air quality levels. The comparison between the simulated and observed mean monthly concentrations revealed an improvement in the pattern of mean monthly concentrations for the “on-line” scenario. Higher values of the index of agreement and correlation for the mean daily values were also identified for the “on-line” scenario in most monitoring sites.

The vision of decarbonization creates the need to design and construct even more energy-efficient buildings. This current target is even more compelling and challenging. The main issue when designing energy-efficient buildings is to identify present and future building energy requirements. A trending method for solving this problem is dynamic building energy simulation. One of the main inputs during energy simulation is weather data. However, the real problem lies in the fact that standard weather data are good at defining the present situation, and they help in designing buildings that behave efficiently under current climate conditions. To achieve the goal of constructing climate proof buildings, the Weather Research and Forecast meteorological model (WRF) was used to predict future climate scenarios. At first, data from previous years (2006–2010) were used to represent the current climate. The model was used to generate future climate data. Thus, results were produced for 5 year periods 2046–2050 and 2096–2100. These data were used for the energy simulation of an office building in Thessaloniki, Greece. The simulation results showed a reduction in heating loads by approximately 20% in the long term and a simultaneous impressive increase in cooling loads by 60%, highlighting the inadequacy of the existing building shell, as well as the heating, ventilation, and air-conditioning (HVAC) system design.

The average PM10 daily levels over the urban area of Thessaloniki, Greece, usually exceed the air quality limits and therefore the improved PM chemical composition and air quality modeling results that will facilitate the design of the most appropriate mitigation measures (e.g., limitations in wood combustion for heating purposes) are essential. The air quality modeling system WRF-CAMx was applied over a 2 × 2 km² horizontal resolution grid covering the greater area of Thessaloniki for the year 2015, when Greece was still confronting the consequences of the financial crisis. The output hourly surface concentrations of twelve PM species at three sites of different environmental type characterization in the city of Thessaloniki were temporally and spatially analyzed. Carbonaceous aerosols (organic and elemental) are the major contributor to total PM10 levels during winter representing a 35–40% share. During summer, mineral aerosols (excluding dust) distribute by up to 48% to total PM10 levels, being the major contributor attributed to road traffic. PM species, during winter, increase in the morning and in the afternoon mainly due to road transport and residential heating, respectively, in addition with the unfavorable meteorological conditions. An underestimation of the primary organic carbon aerosol levels during winter is identified. The application of the modeling system using a different speciation profile for the fine particles emissions from residential heating based on observational data instead of the CAMS emissions profile revealed an improvement in the simulated OC/EC values for which a 50% increase was identified compared to the base run.

The main objective of the present study is the development of a comprehensive methodology for the estimation of the Carbon Footprint (CF) of research project activities and the identification of the best practices that can be followed by project partners within the project implementation to reduce its carbon footprint. The CF methodology is based on the GHG Protocol Guidance and the emissions factors of the Department for Environment Food & Rural Affairs (DEFRA). The emissions sources related to project activities are the following: heating (from fuels combustion), electricity, water, work-commuting, materials, printable deliverables, IT equipment and events. An application study is performed for a research project focusing on the Mediterranean area and it is found that on-site events represent a 41% share of the total CF of the project. The use of public transport and soft mobility by employees can result in a −37% reduction in the CF of work-commuting. The most significant best practices for more sustainable organization of project events, leading to a reduction of −62% and −50% in the CF of the events, are (1) public transportation and soft mobility of the events’ participants to reach the event location within the host city, and (2) the promotion of the use of buses and railway for the international/national travels of participants to/from the event’s host city, respectively. Τhe organization of hybrid events may also reduce the project event’s CF by −50%. The cumulative reduction in the total CF of the project examined from all the CF mitigation scenarios studied, relevant to the energy-efficient target of the EU, the origin of materials used, work-commuting and events (materials used, transportation, hybrid events), is estimated to be −45%.

It is well established that exposure to heat-stress conditions significantly impacts the physiology, health, welfare, and productivity of both sheep and cattle. The aim of this study was to apply the Temperature Humidity Index (THI) in order to assess the impact of future climate conditions on the thermal stress exposure of sheep and cattle in Greece. The Weather Research and Forecasting (WRF) model was used as a high-resolution regional climate model to simulate climate conditions for two decades in Greece at a 10 Km spatial resolution and a 1 h temporal resolution. The WRF model was applied to two emission scenarios, namely SSP2-4.5 (intermediate) and SSP5-8.5 (worst-case). Projections were made for the near-future decade (2046–2055), with the decade (2005–2014) serving as the reference period for comparative analysis. The data analysis indicated that under the SSP2-4.5 emission scenario, the mean temperature is projected to increase by 1.2–1.4 °C and 1.4–1.6 °C across 38% and 58% of the country’s territory, respectively. Increases higher than 1.6 °C are projected across 32% of the Greek territory under the SSP5-8.5 emission scenario. The mean THI (sheep) and mean THI (adj) (cattle) are projected to increase by 5–10% and by 4% across 74% and 82% of the Greek territory, respectively, when considering the SSP2-4.5 emission scenario. Slightly more severe mean heat-stress conditions were projected when considering the SSP5-8.5 emission scenario. The analysis of the hourly THI values showed that sheep and cattle are expected to experience heat-stress conditions during extended periods in the future, in which hot weather will prevail. Specifically, the number of severe/danger heat-stress hours is projected to double in the greater part of the country. To mitigate the adverse effects of climate-change-induced thermal stress on animal productivity, health, and welfare, the implementation of adaptation measures and best management practices is strongly recommended for sheep and cattle farmers. These measures encompass improvements in breeding strategies, livestock housing and microclimate management, nutritional interventions, and the adoption of precision livestock farming technologies. Given the outstanding economic, social, and environmental importance of sheep and cattle farming in Greece, effective adaptation to and mitigation of climate change impacts represent urgent priorities to ensure the long-term sustainability and resilience of the livestock sector.