Spatial and temporal characteristics of air pollutant emissions in Thessaloniki,Greece: investigation of emission abatement measures

The paper presents new detailed emissions inventory for the Greater Area of Thessalonilki, northern Greece, which incorporates a large amount of data on the polluting anthropogenic and biogenic activities in the region, including the location of all individual point, line and area sources along with their daily, weekly and monthly profiles and activity rates. The emission estimate followed both the bottom-up and the top-down approaches. Apart from the base year calculations, scenario estimates are provided for the base year, intended to show the maximum possible benefit of abatement measures and for the future, in order to estimate the evolution of air pollutant emissions in relation to structural changes and land planning. Air pollutant emissions were calculated for an area of 5,120 km2 at two different spatial resolutions (1x1 km2 and 2x2 km2) in order to support air quality simulations in the region. The resulting spatially allocated emission database, which also incorporates elevation and land use data, constitutes a clear improvement in comparison to existing emissions inventories of the area, and the procedure followed can be considered as a 'best practice' guide for developers of urban emissions inventories.     

Exploring the relationship between energy use and economic growth with bivariate models: New evidence from G-7 countries

There is a rapidly growing literature on the interaction between energy use and economic development, with many analysts drawing policy conclusions on the basis of Granger causality tests that involve only an energy and an economic variable. This paper attempts to demonstrate empirically that such studies, although useful for certain applications, may be of limited use for policy purposes. After outlining theoretical and methodological issues associated with such approaches, I apply bivariate energy–economy causality tests for Canada, France, Germany, Italy, Japan, the United Kingdom and the United States, using aggregate and sectoral data and three different modern econometric methods. The results, which are often contradictory or economically implausible, illustrate explicitly that one should be cautious when drawing policy implications with the aid of bivariate causality tests on small samples. I therefore underline the importance of utilizing as large sample sizes as possible and using multivariate models, which are closer to economic theory, accommodate several mechanisms and causality channels and provide a better representation of real-world interactions between energy use and economic growth.