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Francesca Bruno

Bio: Francesca Bruno is an academic researcher from University of Bologna. The author has contributed to research in topics: Spatial dependence & Spatial analysis. The author has an hindex of 9, co-authored 39 publications receiving 298 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, the mixing height was determined from the observed vertical aerosol concentration gradient, and from potential temperature and relative humidity profiles, showing that inter-consistent mixing heights can be retrieved highlighting good correlations between particle dispersion in the atmosphere and meteorological parameters.
Abstract: . Vertical aerosol profiles were directly measured over the city of Milan during three years (2005–2008) of field campaigns. An optical particle counter, a portable meteorological station and a miniaturized cascade impactor were deployed on a tethered balloon. More than 300 vertical profiles were measured, both in winter and summer, mainly in conditions of clear, dry skies. The mixing height was determined from the observed vertical aerosol concentration gradient, and from potential temperature and relative humidity profiles. Results show that inter-consistent mixing heights can be retrieved highlighting good correlations between particle dispersion in the atmosphere and meteorological parameters. Mixing height growth speed was calculated for both winter and summer showing the low potential atmospheric dispersion in winter. Aerosol number size distribution and chemical composition profiles allowed us to investigate particle behaviour along height. Aerosol measurements showed changes in size distribution according to mixing height. Coarse particle profiles (dp>1.6 μm) were distributed differently than the fine ones (dp

67 citations

Journal ArticleDOI
TL;DR: This work proposes a class of air quality indices which are simple to read and easy to understand by citizens and policy-makers and to use simultaneously more than one index of the selected class and to associate a measure of variability with every index.
Abstract: Interest in air quality indices has been increasing in recent years. This is strictly connected with the development and the easy availability of web-communication and on-line information. By means of web pages it is indeed possible to give quick and easy-to-consult information about air quality in a specific area. We propose a class of air quality indices which are simple to read and easy to understand by citizens and policy-makers. They are constructed in order to be able to compare situations that differ in time and space. In particular, interest is focused on situations where many monitoring stations are operating in the same area. In this case, which occurs frequently, air pollution data are collected according to three dimensions: time, space and type of pollutant. In order to obtain a synthetic value, the dimensions are reduced by means of aggregation processes that occur by successively applying some aggregating function. The final index may be influenced by the order of aggregation. The hierarchical aggregation here proposed is based on the successive selection of order statistics, i.e. on percentiles and on maxima. The variety of pollutants measured in each area imposes a standardization due to their different effects on the human health. This evaluation comes from epidemiological studies and influences the final value of the index. We propose to use simultaneously more than one index of the selected class and to associate a measure of variability with every index. Such measures of dispersion account for very important additional information. Copyright © 2002 John Wiley & Sons, Ltd.

45 citations

Journal ArticleDOI
TL;DR: In this article, the authors proposed the use of a model in which non-separability arises from temporal non-stationarity and used it to analyze tropospheric ozone data from the Emilia-Romagna Region of Italy.
Abstract: The past two decades have witnessed an increasing interest in the use of space-time models for a wide range of environmental problems. The fundamental tool used to embody both the temporal and spatial components of the phenomenon in question is the covariance model. The empirical estimation of space-time covariance models can prove highly complex if simplifying assumptions are not employed. For this reason, many studies assume both spatiotemporal stationarity, and the separability of spatial and temporal components. This second assumption is often unrealistic from the empirical point of view. This paper proposes the use of a model in which non-separability arises from temporal non-stationarity. The model is used to analyze tropospheric ozone data from the Emilia-Romagna Region of Italy.

36 citations

Journal ArticleDOI
TL;DR: In this article, Monte Carlo Markov Chain (MCMCMC) algorithms were used to calibrate radar measurements via rain gauge data and make spatial predictions for hourly rainfall, by means of a Bayesian hierarchical framework.
Abstract: Rainfall is a phenomenon difficult to model and predict, for the strong spatial and temporal heterogeneity and the presence of many zero values. We deal with hourly rainfall data provided by rain gauges, sparsely distributed on the ground, and radar data available on a fine grid of pixels. Radar data overcome the problem of sparseness of the rain gauge network, but are not reliable for the assessment of rain amounts. In this work we investigate how to calibrate radar measurements via rain gauge data and make spatial predictions for hourly rainfall, by means of Monte Carlo Markov Chain algorithms in a Bayesian hierarchical framework. We use zero-inflated distributions for taking zero-measurements into account. Several models are compared both in terms of data fitting and predictive performances on a set of validation sites. Finally, rainfall fields are reconstructed and standard error estimates at each prediction site are shown via easy-to-read spatial maps.

28 citations

Journal ArticleDOI
TL;DR: In this paper, a conceptual framework for assessing the statistical properties of a non-stochastic spatial interpolator is developed through the use of design-based finite population inference tools.
Abstract: In this study a conceptual framework for assessing the statistical properties of a non-stochastic spatial interpolator is developed through the use of design-based finite population inference tools. By considering the observed locations as the result of a probabilistic sampling design, we propose a standardized weighted predictor for spatial data starting from a deterministic interpolator that usually does not provide uncertainty measures. The information regarding the coordinates of the spatial locations is known at the population level and is directly used in constructing the weighting system. Our procedure captures the spatial pattern by means of the Euclidean distances between locations, which are fixed and do not require any further assessment after the sample has been drawn. The predictor for any individual value turns in a ratio of design-based random quantities. We illustrate the predictor design-based statistical properties, i.e. asymptotically p-unbiasedness and p-consistency, for simple random sampling without replacement. An application to a couple of environmental datasets is presented, for assessing predictor performances in correspondence of different population characteristics. A comparison with the equivalent non-spatial predictor is presented.

19 citations


Cited by
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Journal ArticleDOI

6,278 citations

Book ChapterDOI
25 Jul 2012

974 citations

DissertationDOI
01 Jan 1983

766 citations

01 Jan 1892
TL;DR: In this paper, the authors explore a hypothesis, based on acIcumulating evidence, regarding the character of inventions likely to issue from the research laboratories of the large industrial corporations.
Abstract: r 9HE purpose of this paper is to explore a hypothesis, based on acIcumulating evidence, regarding the character of inventions likely to issue from the research laboratories of the large industrial corporations. Simply put, this hypothesis may be stated as follows: with few exceptions, the large industrial laboratories are likely to be minor sources of major (radically new and commercially or militarily important) inventions; rather they are likely to be major sources of essentially "improvement" inventions. Put more precisely, the hypothesis states that the proportion of all minor inventions originating in the large industrial laboratories is likely to exceed the proportion of all major inventions originating in these laboratories. Note that the stress on the relative importance of these laboratories as sources of improvement inventions is not necessarily a denigration of the economic importance of this contribution. The cumulative effect of these improvement inventions may be, and often has been, of substantial importance over long periods of time for advancing technology, investment opportunities, and economic growth. The stress on improvement inventions as the principal product of the research laboratories of the large industrial corporations is meant simply to emphasize that, whatever the importance of their contributions, most of the latter is not likely to involve radically new inventive activity. I cannot claim originality for this hypothesis. After it suggested itself in the course of my investigations, I discovered that others, some of them in the most unlikely positions,2 had earlier said much the same thing. But, apart from occasional remarks, I can find no discussions attempting to explain or justify it. And because, if reasonably accurate, it has numerous ramifications, I have felt the need to set down an extended analysis of 1 I wish to thank members of the Seminar on Law and Technology, sponsored by the University of Wisconsin Law School under the auspices of the Ford Foundation, for their many helpful comments on this paper. Especially do I wish to thank Professors Jacob Schmookler, Robert Merrill, John Stedman, Harrison White, and John Heath. 2 See particularly the statement quoted below (p. 114) of D)r. Frank Jewett, former president of Bell Laboratories.

689 citations