Water for utilities: climate change impacts on water quality and water availability for utilities in Europe

This report provides an assessment of the consequences of changing water availability for production of drinking water, the manufacturing industry and power production in Europe, due to climate change and socio-economic developments. The report is based up on projections of demographic and socio-economic trends and climate change impacts, according to the SRES A2 and B1 scenario’s also used by IPC

What's Behind Acoustic Peaks in the Cosmic Microwave Background Anisotropies

We give a brief review of the physics of acoustic oscillations in Cosmic Microwave Background (CMB) anisotropies. As an example of the impact of their detection in cosmology, we show how the present data on CMB angular power spectrum on sub-degree scales can be used to constrain dark energy cosmological models.Comment: 6 pages, proceedings to the TAUP2001 conference, LNGS, Italy, Sept. 200

Goodness-of-Fit Tests to study the Gaussianity of the MAXIMA data

Goodness-of-Fit tests, including Smooth ones, are introduced and applied to detect non-Gaussianity in Cosmic Microwave Background simulations. We study the power of three different tests: the Shapiro-Francia test (1972), the uncategorised smooth test developed by Rayner and Best(1990) and the Neyman's Smooth Goodness-of-fit test for composite hypotheses (Thomas and Pierce 1979). The Smooth Goodness-of-Fit tests are designed to be sensitive to the presence of ``smooth'' deviations from a given distribution. We study the power of these tests based on the discrimination between Gaussian and non-Gaussian simulations. Non-Gaussian cases are simulated using the Edgeworth expansion and assuming pixel-to-pixel independence. Results show these tests behave similarly and are more powerful than tests directly based on cumulants of order 3, 4, 5 and 6. We have applied these tests to the released MAXIMA data. The applied tests are built to be powerful against detecting deviations from univariate Gaussianity. The Cholesky matrix corresponding to signal (based on an assumed cosmological model) plus noise is used to decorrelate the observations previous to the analysis. Results indicate that the MAXIMA data are compatible with Gaussianity.Comment: MNRAS, in pres