DECOMPOSITION ANALYSIS OF AIR POLLUTANTS DURING THE TRANSITION AND POST-TRANSITION PERIODS IN THE CZECH REPUBLIC

摘要

We examine the main driving forces of significant reductions in air pollutants thatoccurred during the transition of the Czech economy towards a market economy in the 1990sand how these driving forces affected emissions volumes across the post-transition period to2016. Using Logarithmic Mean Divisia Index decomposition (Ang & Liu, 2001), westatistically decompose annual changes in the emission levels from large stationary emissionsources of four types of air quality pollutants, including sulphur dioxide, carbon monoxide,nitrogen oxides and particulate matters over the period 1990–2016. While most of previousdecomposition studies have been decomposing emissions into scale, structure and emissionintensity factors, a unique environmental dataset allows us to further decompose the emissionper output effect into [i] the emission-fuel factor, [ii] the fuel-mix factor, and [iii] the fuelintensityfactor, yielding a 5-factor decomposition. We find that the largest drop in emissionsof all four pollutants occurred up to 1999 when the emissions decreased cumulatively by 74 %at least. In this period, the firms faced new competitive environment and were exposed to strictnew command and control regulation – as a result, negative emission-fuel factor was the keydriver of the emission reduction. However, the fuel-intensity effect contributed most toreduction of SO2, NOx and PM emission in the first 3 years after the Velvet revolution (1990-1992). Since 2008, activity, structure, fuel-intensity and emission-fuel factors have contributedto emission changes by similar magnitudes, but in different directions. In the last two years, theemission-fuel factor effect has become important again, as the large stationary emission sourceswere required to comply with new emission limits set by the EU Industrial Emissions Directive.In order to examine the effect of the key LMDI parameters on the decomposition outcome, weperform a sensitivity analysis to decompose SO2 emissions on different numbers of effects (3-,4- and 5-factors) and when different sectoral detail is assumed.