Change of heating fuel consumption patterns produced by the economic crisis in Greece

University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

Abstract: The economic crisis in Greece resulted in a change in residential heating fuels utilized, which in turn resulted in a change of air quality over Greater Athens Area. The aim of this study was to investigate the effects of economic crisis in air quality over Attica by examining the change in air pollutants’ concentrations before, during, and after the onset of the economic crisis in Greece and to associate this change with the change in fuels used for residential heating. For this purpose, I analyzed six MODIS L1B datasets with 500m spatial resolution, one for each year studied, MODIS AOT and NDVI products, at 10 km and 500 m spatial resolution respectively. Additionally, I used AQMS measurements and CORINE 2000 Land Cover dataset. To densify the ground monitoring network, virtual stations were identified according to Narashid et al (2006) criteria. Through OLS regressions, air pollutants’ concentration were estimated for the virtual stations and, subsequently, for the whole map of Great Athens Area (GAA) for the chosen time periods. Subsequently, the association between the change in fuel consumption and the change in pollutant concentrations between the examined periods was performed, based on Kakaras et al (2013) emissions ratios for each fuel utilized in residential heating that indirectly indicate fuel types utilized in the residential heating systems. Primary results show that during the whole period examined (2007-2012) SO2 concentrations were increased in most parts of GAA, while NO2 and PM10 were decreased. CO concentrations were stable in most zones of GAA. Where the fuels used for residential heating are concerned, the use of wood and pellet has increased in most urban areas of GAA, while the use of heating oil and natural gas appear to be decreased. Keywords: Economic Crisis, Air Quality, Satellite Data, Virtual Stations, Regression Analysis, Air pollutants mapping, anthropogenic factors.

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