Measurements of air temperature and humidity in the urban canopy layer during July 2009 in 26 sites in Athens, Greece, allowed for the mapping of the hourly spatiotemporal evolution of the urban heat island (UHI) effect. City districts neighboring to the mountains to the east were the hottest during the afternoon, while being among the coolest during the early morning hours. While during the early morning some coastal sites were the hottest, the warm air plume slowly moved to the densely urbanized center of the city until 14:00-15:00, moving then further west, to the Elefsis industrial area in the afternoon. Results from the UrbClim model agree fairly well with the observations. Satellite-derived land surface temperature (LST) data from AATSR, ASTER, AVHRR and MODIS, for pixels corresponding to ground stations measuring Tair, showed that LST can be up to 5K lower than the respective Tair during nighttime, while it can be up to 15K higher during the rest of the day. Generally, LST during late afternoon as acquired from AATSR is very near to Tair for all stations and all days, i.e., the AATSR LST afternoon retrieval can be used as a very good approximation of Tair. The hourly evolution of the spatial Tair distribution was almost the same during days with NE Etesian flow as in days with sea breeze circulation, indicating that the mean wind flow was not the main factor controlling the diurnal UHI evolution, although it influenced the temperatures attained. No unambiguous observation of the urban moisture excess (UME) phenomenon could be made.
The Mediterranean is recognized among the most responsive regions to climate change, with annual temperatures projected to increase by 1–5 °C until 2100. Large cities may experience an additional stress discomfort due to the Urban Heat Island (UHI) effect. In the present study, the WRF-ARW numerical weather prediction model was used to investigate the climate change impact on UHI for two Mediterranean cities, Rome and Thessaloniki. For this purpose, three 5-year time-slice simulations were conducted (2006–2010, 2046–2050, 2096–2100) under the Representative Concentration Pathway (RCP) 8.5 emission scenario, with a spatial resolution of 2 km. In order to comprehensively investigate the urban microclimate, we analyze future simulation data across sections crossing urban/non-urban areas, and after grouping them into three classes depending on the location of the grid cells. The urban areas of both cities present increased average minimum temperature (Tmin) in winter/summer compared to other rural areas, with an UHI of ~+1.5–3 °C on average at night/early morning. Considering UHI under future climate change, we found no significant variations (~±0.2 °C). Finally, we found that the numbers of days with Tmin ≥ 20 °C will mostly increase in urban coastal areas until 2100, while the largest increase of minimum Discomfort Index (DImin) is expected in urban low-ground areas.
The main aim of this study is the identification of the most appropriate measures and policies to combat particulate air pollution in the city of Thessaloniki, Greece through a methodology including the calculation of emissions by sector and the application of an air quality modeling system. The identification of the current air quality situation showed that the exceedances of the mean PM10 daily levels occur during the cold winter months with residential heating being the major contributor representing a 73% share of total PM10 emissions. Moreover, the effect of the biomass consumption for heating purposes on PM10 concentrations has been verified and quantified by implementing a regression model identifying that a PM10 emissions reduction by 45% would result in the elimination of the exceedances of the mean PM10 daily values. Based on the above, a set of cost-effective measures and policies were defined and their impact on PM10 emissions was estimated. Finally, the air quality modeling system was applied for the mitigation scenarios selected, leading to a significant reduction of 67% in the number of exceedances observed and ensuring compliance with the limit of 35 exceedances of the daily value limit per year pursuant to European Legislation.
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.
Although there is a growing interest in the association between ambient temperatures and mortality, little evidence is available for Thessaloniki, the second largest city of Greece. In this study, we present an assessment of the effects of temperature on daily mortality from 2006 to 2016 in the urban area of Thessaloniki, by describing the exposure-lag-response association between temperature and cause-specific mortality with the use of a distributed lag non-linear model (DLNM). A J-shaped relationship was found between temperature and mortality. The highest values of risk were evident for respiratory (RR > 10) and cardiovascular causes (RR > 3), probably due to the fact that health status of individuals with chronic respiratory and cardiovascular diseases rapidly deteriorates during hot periods. Cold effects had longer lags of up to 15 days, whereas heat effects were short-lived, up to 4 days. Percentage change in all- and cause-specific mortality per 1 °C change above and below Minimum Mortality Temperature showed a larger increase for all-cause mortality in heat (1.95%, 95% CI: 1.07–2.84), in contrast to a smaller increase in cold (0.54%, 95% CI: 0, 1.09). Overall, 3.51% of all-cause deaths were attributable to temperature, whereas deaths attributed to heat (2.34%) were more than deaths attributed to cold (1.34%). The findings of this study present important evidence for planning public-health interventions, to reduce the health impact of extreme temperatures.