One of the main objectives of the European Union Emission Trading Scheme is the establishment of a market price level for allowances that show to European CO2 emitting installations the environmental impact of their polluting activities. The aim of this paper is to focus on the daily price changes during 2005 in an attempt to examine the underlying rationality of pricing behaviour. Specifically, we study the effect of those weather and non-weather variables that academic and market agents consider as the major determinants of the of CO2 price levels. The results show that the energy sources are the principal factors in the determination of CO2 price levels, and that only extreme temperatures influence them.

Weather has a significant impact on different sectors of the economy. One of the most sensitive is the electricity market, because power demand is linked to several weather variables, mainly the air temperature. This work analyzes the relationship between electricity load and daily air temperature in Spain, using a population-weighted temperature index. The electricity demand shows a significant trend due to socioeconomic factors, in addition to daily and monthly seasonal effects that have been taken into account to isolate the weather influence on electricity load. The results indicate that the relationship is nonlinear, showing a “comfort interval” of ±3°C around 18°C and two saturation points beyond which the electricity load no longer increases. The analysis has also revealed that the sensitivity of electricity load to daily air temperature has increased along time, in a higher degree for summer than for winter, although the sensitivity in the cold season is always more significant than in th... Abstract Weather has a significant impact on different sectors of the economy. One of the most sensitive is the electricity market, because power demand is linked to several weather variables, mainly the air temperature. This work analyzes the relationship between electricity load and daily air temperature in Spain, using a population-weighted temperature index. The electricity demand shows a significant trend due to socioeconomic factors, in addition to daily and monthly seasonal effects that have been taken into account to isolate the weather influence on electricity load. The results indicate that the relationship is nonlinear, showing a “comfort interval” of ±3°C around 18°C and two saturation points beyond which the electricity load no longer increases. The analysis has also revealed that the sensitivity of electricity load to daily air temperature has increased along time, in a higher degree for summer than for winter, although the sensitivity in the cold season is always more significant than in th...

A split-window equation is derived for land surface temperature, yielding T = T₄ + A(T₄ − T₅) + B(ε), where T is the true surface temperature, T₄ and T₅ are the brightness temperatures measured in AVHRR channels 4 and 5, A is a coefficient related to the atmospheric transmittances in AVHRR channels 4 and 5, being dependent on the atmosphere type and independent on surface emissivity, and B(ε) takes into account the emissivity effect, which depends on both the channel surface emissivities (ε₄ and ε₅) and the atmosphere type. The atmospheric dependence of split-window coefficients, A and B(ε), is discussed by means of satellite measurements simulations and in situ data. It is shown that linear, global-scale algorithms can produce inaccurate estimates of surface temperature when they are applied to areas of reduced atmospheric variability. A simple, non-linear split-window algorithm has been proposed, in which A = a₀+ a₁(T₄− T₅). The constants a₀and a₁ have been calculated from a set of in situ and coincident satellite measurements of sea surface temperatures taken over a wide range of latitudes. A linear split-window algorithm optimized for mid-latitude conditions has been also derived. The combined effects of atmospheric attenuation and surface emissivity on T₄ − T₅ have been discussed. Moreover, the theoretical results derived are applied to a NOAA-9 image, for which a procedure for estimating the channel emissivity difference (ε₄ − ε₅) using satellite sensor data is suggested.