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H, C, and O stable isotope ratios and the elemental profile of 267 olive oils and 314 surface waters collected from 8 European sites are presented and discussed. The aim of the study was to investigate if olive oils produced in areas with different climatic and geological characteristics could be discriminated on the basis of isotopic and elemental data. The stable isotope ratios of H, C, and O of olive oils and the ratios of H and O of the relevant surface waters correlated to the climatic (mainly temperature) and geographical (mainly latitude and distance from the coast) characteristics of the provenance sites. It was possible to characterize the geological origin of the olive oils by using the content of 14 elements (Mg, K, Ca, V, Mn, Zn, Rb, Sr, Cs, La, Ce, Sm, Eu, U). By combining the 3 isotopic ratios with the 14 elements and applying a multivariate discriminant analysis, a good discrimination between olive oils from 8 European sites was achieved, with 95% of the samples correctly classified into the production site.

Spatial estimations are increasingly used to estimate geocoded ambient particulate matter (PM) concentrations in epidemiologic studies because measures of daily PM concentrations are unavailable in most U.S. locations. This study was conducted to a) assess the feasibility of large-scale kriging estimations of daily residential-level ambient PM concentrations, b) perform and compare cross-validations of different kriging models, c) contrast three popular kriging approaches, and d ) calculate SE of the kriging estimations. We used PM data for PM with aerodynamic diameter ≤ 10 µm (PM 10 ) and aerodynamic diameter ≤ 2.5 µm (PM 2.5 ) from the U.S. Environmental Protection Agency for the year 2000. Kriging estimations were performed at 94,135 geocoded addresses of Women's Health Initiative study participants using the ArcView geographic information system. We developed a semiautomated program to enable large-scale daily kriging estimation and assessed validity of semivariogram models using prediction error (PE), standardized prediction error (SPE), root mean square standardized (RMSS), and SE of the estimated PM. National-and regional-scale kriging performed satisfactorily, with the former slightly better. The average PE, SPE, and RMSS of daily PM 10 semivariograms using regular ordinary kriging with a spherical model were 0.0629, -0.0011, and 1.255 µg/m 3 , respectively; the average SE of the estimated residential-level PM 10 was 27.36 µg/m 3 . The values for PM 2.5 were 0.049, 0.0085, 1.389, and 4.13 µg/m 3 , respectively. Lognormal ordinary kriging yielded a smaller average SE and effectively eliminated out-of-range predicted values compared to regular ordinary kriging. Semiautomated daily kriging estimations and semivariogram cross-validations are feasible on a national scale. Lognormal ordinary kriging with a spherical model is valid for estimating daily ambient PM at geocoded residential addresses.Abbreviations: Natl, national-scale kriging; MN, kriging in middle north region; NE, kriging in northeast region; NW, kriging in northwest region; SE, kriging in southeast region; SW, kriging in southwest region.

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[1] Mountains within alpine regions can have a significant influence on the geographic distribution of precipitation and on local-to regional-scale climatic and meteorological conditions. Consequently, the oxygen and hydrogen isotope compositions of precipitation are affected by alpine topography as well. The Austrian Network of Isotopes in Precipitation, one of the oldest and densest networks in the world, is therefore an excellent source of isotope data of the last 30 years for investigating the complex processes governing the isotopic composition of precipitation in alpine regions. Fractionation during phase change processes leads to significant isotopic variation in precipitation. Here we show that the spatial isotopic variability, especially in alpine regions, is to a large extent due to nonequilibrium fractionation. Additionally, we conclude that meteorological conditions prevailing at the sampling site are mainly responsible for the observed seasonal pattern in deuterium excess. These results are validated by stepwise multiple regression as well as by applying an empirical model for deuterium excess, which is an indicator of the differential behavior of D and18 O values in vapor and precipitation. The present results enhance the development of models based on detailed statistical assessment of local climatic conditions to improve the quantitative interpretation of isotope data for paleoclimatology delivered by glacial ice of alpine regions.